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packed 12000000 tokens from 182016 ids -> /tmp/dev_train.npy
HELDOUT_PPL 476.714  loss 6.1669  train_s 55  /tmp/dev_train.npy
(dev PPL on multi_dev; official uses a hidden disjoint sample of the same HQ domain)

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  232       05:06  0.0  0.0 node /usr/bin/codex exec --dangerously-bypass-approvals-and-sandbox --skip-git-repo-check --model azure_ai/gpt-5.6-sol --json --enable unified_exec -c model_reasoning_effort=high -c model_reasoning_effort=high -c request_max_retries=12 -c stream_max_retries=12 -c stream_idle_timeout_ms=600000 -- # Task: Curate a raw web corpus to train the best small language model  ## Context You are assembling the pretraining data for a small language model. You have a large pool of **raw web documents** at `/workspace/data/pool.jsonl` — one JSON object per line: `{"id": <int>, "text": "..."}`. The documents are unlabeled. The pool holds **182,016 documents (~200M GPT-2 tokens total)**.  Compute is fixed: the model is trained on a **fixed budget of 12,000,000 tokens** — only ~6% of the pool, far smaller than the whole thing. So you cannot train on everything: you must decide *which* documents are worth training on. The training pipeline tokenizes your selection (GPT-2 BPE) in priority order and stops once it has accumulated 12M tokens.  ## Goal Curate the pool: choose the documents that, trained on under the fixed budget, produce the **best language model**. Quality is measured by **held-out perplexity on a BROAD, multi-domain high-quality English target** — equal parts encyclopedic (Wikipedia), general high-quality web prose, news, and technical Q&A. This is your disclosed target: select data that makes the model good across *all* of these registers, not just one. Lower perplexity is better.  ## Deliverables 1. `/workspace/submission/selection.json` — a JSON list of pool `id`s to train    on, in **priority order** (best first). The training pipeline consumes your    list in order until the **12M-token** budget is filled, then trains. Provide    enough ids to cover at least 12M tokens (a few hundred MB of text is ample);    ids beyond the budget are simply unused. 2. `/workspace/submission/curate.py` — the reproducible script that produced    your selection from a stated criterion (not a hand-picked id list). 3. `/workspace/claim.md` — Hypothesis / Mechanism (predict an observable other    than the final perplexity) / Falsification / Transfer.  ## Resources - The **frozen training script** is provided (`/workspace/train_nano.py`, with   `model.py`). It trains a ~30M-parameter GPT from scratch on a token budget with   fixed hyperparameters. **You may run it to evaluate a candidate selection**   against a dev target (`/workspace/data/multi_dev.npy`) — one run is ~60s on the   GPU — but you **cannot change it**; the official run uses an identical frozen   copy. The only thing you control is the data selection. - Standard GPU sandbox (Python, PyTorch, transformers). How you assess document   quality is entirely up to you (filters, classifiers, heuristics, a model, etc.). - Your session ends when the wall-clock budget runs out — check   `/workspace/.timer/remaining_secs` at any point for the authoritative time left   (don't assume a fixed number of hours). Every training run you do comes out of   that budget. - No internet. The pool's documents are freshly assembled; you cannot look up   any quality labels — any quality signal must come from your own analysis.  ## How you are scored Official: your selection fills the fixed token budget, the frozen script trains the 30M GPT from scratch, and the verifier measures the **absolute held-out perplexity on the hidden high-quality target** (a different sample from the disclosed domain than the dev set). That perplexity is your score. **Lower is better** — the goal is simply to push held-out perplexity as low as you can.  The verifier reports the raw perplexity and does no normalization. For reference and for a separate downstream normalization step, the benchmark records two fixed anchors: a **baseline** of held-out perplexity from a random selection (the do-nothing reference), and a **theoretical best** of perplexity 1 (the perplexity floor, unreachable in practice). Aim to get your held-out perplexity well below the random baseline.  ## Constraints - `selection.json` must be produced by `curate.py` from a stated criterion; an   opaque hand-picked id list fails the publishability check even if it scores well. - A selection with duplicate or out-of-range ids, or too few tokens to fill the   budget, is marked invalid (no score recorded) and excluded from ranking, so it   can't win and doesn't distort averages. 
  240       05:06  3.0  0.0 /usr/lib/node_modules/@openai/codex/node_modules/@openai/codex-linux-x64/vendor/x86_64-unknown-linux-musl/bin/codex exec --dangerously-bypass-approvals-and-sandbox --skip-git-repo-check --model azure_ai/gpt-5.6-sol --json --enable unified_exec -c model_reasoning_effort=high -c model_reasoning_effort=high -c request_max_retries=12 -c stream_max_retries=12 -c stream_idle_timeout_ms=600000 -- # Task: Curate a raw web corpus to train the best small language model  ## Context You are assembling the pretraining data for a small language model. You have a large pool of **raw web documents** at `/workspace/data/pool.jsonl` — one JSON object per line: `{"id": <int>, "text": "..."}`. The documents are unlabeled. The pool holds **182,016 documents (~200M GPT-2 tokens total)**.  Compute is fixed: the model is trained on a **fixed budget of 12,000,000 tokens** — only ~6% of the pool, far smaller than the whole thing. So you cannot train on everything: you must decide *which* documents are worth training on. The training pipeline tokenizes your selection (GPT-2 BPE) in priority order and stops once it has accumulated 12M tokens.  ## Goal Curate the pool: choose the documents that, trained on under the fixed budget, produce the **best language model**. Quality is measured by **held-out perplexity on a BROAD, multi-domain high-quality English target** — equal parts encyclopedic (Wikipedia), general high-quality web prose, news, and technical Q&A. This is your disclosed target: select data that makes the model good across *all* of these registers, not just one. Lower perplexity is better.  ## Deliverables 1. `/workspace/submission/selection.json` — a JSON list of pool `id`s to train    on, in **priority order** (best first). The training pipeline consumes your    list in order until the **12M-token** budget is filled, then trains. Provide    enough ids to cover at least 12M tokens (a few hundred MB of text is ample);    ids beyond the budget are simply unused. 2. `/workspace/submission/curate.py` — the reproducible script that produced    your selection from a stated criterion (not a hand-picked id list). 3. `/workspace/claim.md` — Hypothesis / Mechanism (predict an observable other    than the final perplexity) / Falsification / Transfer.  ## Resources - The **frozen training script** is provided (`/workspace/train_nano.py`, with   `model.py`). It trains a ~30M-parameter GPT from scratch on a token budget with   fixed hyperparameters. **You may run it to evaluate a candidate selection**   against a dev target (`/workspace/data/multi_dev.npy`) — one run is ~60s on the   GPU — but you **cannot change it**; the official run uses an identical frozen   copy. The only thing you control is the data selection. - Standard GPU sandbox (Python, PyTorch, transformers). How you assess document   quality is entirely up to you (filters, classifiers, heuristics, a model, etc.). - Your session ends when the wall-clock budget runs out — check   `/workspace/.timer/remaining_secs` at any point for the authoritative time left   (don't assume a fixed number of hours). Every training run you do comes out of   that budget. - No internet. The pool's documents are freshly assembled; you cannot look up   any quality labels — any quality signal must come from your own analysis.  ## How you are scored Official: your selection fills the fixed token budget, the frozen script trains the 30M GPT from scratch, and the verifier measures the **absolute held-out perplexity on the hidden high-quality target** (a different sample from the disclosed domain than the dev set). That perplexity is your score. **Lower is better** — the goal is simply to push held-out perplexity as low as you can.  The verifier reports the raw perplexity and does no normalization. For reference and for a separate downstream normalization step, the benchmark records two fixed anchors: a **baseline** of held-out perplexity from a random selection (the do-nothing reference), and a **theoretical best** of perplexity 1 (the perplexity floor, unreachable in practice). Aim to get your held-out perplexity well below the random baseline.  ## Constraints - `selection.json` must be produced by `curate.py` from a stated criterion; an   opaque hand-picked id list fails the publishability check even if it scores well. - A selection with duplicate or out-of-range ids, or too few tokens to fill the   budget, is marked invalid (no score recorded) and excluded from ranking, so it   can't win and doesn't distort averages. 
  712       02:26 96.0  0.4 python explore_rank.py
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domain 0 docs 1571 chunks 1077
domain 1 docs 203 chunks 395
domain 2 docs 424 chunks 499
domain 3 docs 359 chunks 385
fit vocab 48072 counts 959360 5911912 domains [199078, 316862, 287097, 156323]
saved /workspace/scores.pkl 182016

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q quant [-3.36078357 -0.74882445 -0.33083236 -0.07687767 -0.01702954  0.10223121
  1.53428844]
qual [-6.36294378 -0.85035844  0.29042515  0.73975932  0.80689021  0.92555584
  1.72449295]
domains [ 20780 142533   8816   9887] [0.13519707 0.70121491 0.09950143 0.06408659]
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D 2 [(108673, 1.46, [0.0, 0.0, 1.0, 0.0], 570), (58452, 1.42, [0.0, 0.0, 1.0, 0.0], 206), (41186, 1.32, [0.0, 0.0, 1.0, 0.0], 510), (43758, 1.3, [0.02, 0.0, 0.98, 0.0], 278), (102696, 1.3, [0.0, 0.0, 1.0, 0.0], 254), (76950, 1.3, [0.02, 0.0, 0.98, 0.0], 379), (69836, 1.29, [0.13, 0.0, 0.87, 0.0], 222), (37522, 1.29, [0.0, 0.0, 1.0, 0.0], 184), (44450, 1.27, [0.02, 0.0, 0.98, 0.0], 249), (18843, 1.23, [0.0, 0.0, 0.99, 0.0], 276), (97014, 1.22, [0.01, 0.01, 0.99, 0.0], 342), (30265, 1.22, [0.1, 0.0, 0.9, 0.0], 299)]
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### 2027 From Wikipedia, the free encyclopedia |February 24, 1882 - December 16, 1948 (aged 66)| General Hayao Tada |Place of birth||Sendai, Miyagi, Japan| |Allegiance||Empire of Japan| |Service/branch||Imperial Japanese Army| |Years of service||1903 -1945| |Commands held||China Garrison Army.| IJA 11th Division, IJA Third Army, North China Area Army Second Sino-Japanese War |Awards||Order of the Golden Kite (2nd class)| Tada graduated from the 25th class of the Army War College (Japan) in 1913. He serve

### 18843 This is Modi’s ‘Start-up India’, ‘Make in India’, he says on charges against Jay Shah Congress vice president Rahul Gandhi on Monday questioned Prime Minister Narendra Modi’s “silence” on a media report alleging that a company owned by the son of BJP president Amit Shah saw a staggering increase in turnover after the party came to power at the Centre. On Day Two of his three-day ''yatra'' in poll-bound Gujarat, Mr. Gandhi accused the National Democratic Alliance government of promoting crony cap

### 28954 U.S. intelligence officials will meet with congressional lawmakers about North Korea's alleged nuclear cooperation with Syria Thursday on Capitol Hill. High-ranking U.S. officials are telling reporters the lawmakers will be shown video of North Koreans working at a suspected nuclear reactor site in Syria. The video also reportedly shows the reactor's design was identical to the North Korean reactor at Yongbyon. The suspected reactor site was destroyed by Israeli warplanes last September. Damascu

### 30265 . S. Gill |Dr. Manmohan Singh Gill| |Chief Election Commissioner of India| |Preceded by||T.N. Seshan| |Succeeded by||J.M. Lyngdoh| |Born||14 June 1936| Dr. M. S. Gill (born 14 June 1936) is an Indian politician, of the Indian National Congress party, has served as the Minister of Youth Affairs and Sports. He represents Punjab in the Rajya Sabha, the upper house of the Indian Parliament. Early Life and Career In 1958 he joined the Indian Administrative Services and served in administration at var

### 36908 Thomas Robert Gore Browne |Birthplace:||Aylesbury, Buckinghamshire, England| |Death:||Died in London, England| |Managed by:||Alisdair James Smyth| About Colonel Sir Thomas Robert Gore Browne KCMG CB Wikipedia Biographical Summary Colonel Sir Thomas Robert Gore Browne KCMG CB (3 July 1807 – 17 April 1887) was a British colonial administrator, who was Governor of St Helena, Governor of New Zealand, Governor of Tasmania and Governor of Bermuda. Browne was born in Aylesbury, Buckinghamshire, England

### 37522 Prime Minister Imran Khan on Thursday congratulated India’s premier Narendra Modi on his victory in the country's national elections. "I congratulate Prime Minister Modi on the electoral victory of BJP and allies. Look forward to working with him for peace, progress and prosperity in South Asia," the prime minister said on Twitter. I congratulate Prime Minister Modi on the electoral victory of BJP and allies. Look forward to working with him for peace, progress and prosperity in South Asia— Imra

### 38082  (AP) - The leaders of a congressional inquiry into Russia's efforts to sway the U.S. election called on the Justice Department Wednesday to produce any evidence that supports President Donald Trump's explosive wiretapping allegation. Declaring that Congress "must get to the bottom" of Trump's claim, Sens. Lindsey Graham, R-S.C., and Sheldon Whitehouse, D-R.I., asked Acting Deputy Attorney General Dana Boente and FBI Director James Comey to produce the paper trail created when the Justice Depart

### 41186 Amarnath Yatra 2017 Amarnath Yatra 2017 News Jammu and Kashmir police said three people, alleged conspirators in the 10 July attack on Amarnath pilgrims, have been arrested by its SIT As many as 813 pilgrims on Thursday paid obeisance at the cave shrine of Amarnath in south Kashmir hills, an official said. Over 300 pilgrims left Jammu for the 3,888-metre-high Amarnath cave shrine of Lord Shiva in south Kashmir Himalayas, amid tight security. Over 1,002 pilgrims left Jammu for the Amarnath cave s

### 43758 vel (Maharashtra), June 14 (ANI): A magistrate's court in Panvel, Maharashtra, on Sunday extended suspended senior Nationalist Congress Party (NCP) leader Padamsinh Patil's CBI custody to June 20. Patil has been declared a prime accused in the 2006 murder of Congress leader Pavan Raje Nimbalkar. Nimbalkar was shot dead by two gunmen at Kalamboli in Navi Mumbai where he was called to discuss a business deal. The judicial remand of two other co-accused - businessmen Mohan Shukla and Satish Mandade

### 44450 South Africa came back strongly in the second match of the three-match ODI series in Johannesburg Sunday to beat Bangladesh by seven wickets. With this win, the hosts levelled the series 1-1. Both the teams will take on each other in the series decider on March 23 in Centurion. In the day’s match, Bangladesh posted 194 for nine after choosing to bat first. In a must-win second ODI game, South Africa chased down the target in 37.2 overs, with Quinton de Kock (62) and Kyle Verreynne (58*) killing 

### 46611 <|endoftext|>The Grass Crown (novel) First US edition |Publisher||William Morrow (US) |Media type||Print (Hardback & Paperback)| |Preceded by||The First Man in Rome| |Followed by||Fortune's Favourites| The novel opens shortly after the action of The First Man in Rome. Gaius Marius and Lucius Cornelius Sulla eat dinner together with their wives, and discuss the threat presented by Mithridates VI of Pontus and Tigranes II of Armenia. Although these two powerful Eastern rulers would eventually decl

### 49882 .<|endoftext|>Russia said on Friday it strongly disagreed with changes to its draft UN Security Council resolution on Syria that are being promoted by Western states, AFP "Unfortunately, the West's approach radically differs from ours," Deputy Foreign Minister Gannady Gatilov was quoted as saying by Interfax. "Judging by the contents of their proposed amendments, their goal is clearly aimed at removing (President Bashar) al-Assad's regime in Damascus," he said, Russia and China vetoed a European

### 54115  that a final decision to remove Sudan from the terrorism list must be approved by the White House. But President Trump is not expected to wait for Congress to act. With six weeks before the election, Mr. Trump has cited the warming ties among once-rival states in the Middle East and North Africa as an example of his administration’s diplomatic prowess. Five additional countries are considering formal relations with Israel, the president said on Sept. 15, and officials have said they include Sud

### 56890  relates two-year nightmare in captivity NAUSHAHRO FEROZE, Aug 15: A young girl, Ms Parveen who was kidnapped from Khahi Jalalji village some two years ago reached her home along with a one-and-half year old son. The father of Parveen, Mohammad Ramzan Rajpar, a resident of Khahi Jalalji village near Padidan, lodged an FIR with Padidan police station on Friday. According to the FIR and what Ms Parveen told journalists, she was kidnapped by some men — Nazir, son of Ghulam Rasool; Banho, son of Khi

### 58452 <|endoftext|>New Delhi: Five new Supreme Court judges were today sworn in, taking the top court’s strength to 28, including the Chief Justice of India. Justices Sanjay Kishan Kaul, Navin Sinha, Mohan M Shantanagoudar, Deepak Gupta and S Abdul Nazeer were administered the oath of office by CJI J S Khehar this morning. Justice Kaul was the Chief Justice of Madras High Court. He had previously served as Chief Justice of the Punjab and Haryana High Court and a judge at the Delhi High Court. Justice 

### 61536 <|endoftext|>Disgraced former Rep. Anthony Weiner plans to plead guilty Friday in federal court to a charge of transferring obscene material to a minor. A public relations firm for Weiner’s lawyer confirmed to Fox News that he will plead guilty, and the FBI told Fox News that Weiner surrendered on Friday morning, Fox News reports. The FBI began investigating Weiner in September after a 15-year-old North Carolina girl told a tabloid news site that she and the former politician had exchanged lewd 

### 61757 �The United States will encourage a peace and really a great peace deal” between Israel and the Palestinians, but they have to negotiate it themselves, Trump said at a joint press conference with Netanyahu in Washington, DC on Wednesday.“Both sides will have to make compromises.” “I want the Israeli people to know that the US stands with Israel in the struggle against terrorism, ”the US president added, calling Israel a “cherished ally.” “Israel has no better ally than the US,” Netanyahu said, “

### 66305 Bradford West Respect MP George Galloway has defended his controversial claim that a sex assault allegation against WikiLeaks campaigner Julian Assange amounted to no more than bad "sexual etiquette". Mr Galloway provoked a furious response from women's groups after he said in a video podcast that even if the complaints made against Mr Assange by two women in Sweden were true, they did not constitute rape. But in a statement today, the MP said he did not believe the authorities in Britain would 

### 68995 ||This article includes a list of references, but its sources remain unclear because it has insufficient inline citations. (February 2011)| Quintus Fabius Maximus Verrucosus Cunctator (ca. 280 BC – 203 BC) was a Roman politician and general, born in Rome around 280 BC and died in Rome in 203 BC. He was Roman Consul five times (233 BC, 228 BC, 215 BC, 214 BC and 209 BC) and was twice Dictator, in 221 and again in 217 BC. He reached the office of Roman Censor in 230 BC. His agnomen Cunctator (cogn

### 69836 oor ul HaqBaramulla, Aug 10: Army on Friday said the five militants killed in upper reaches of Rafiabad during two-day gunfight were all foreigners and belonged to Lashkar-e-Toiba. Addressing a press conference at Pohrupeth Handwara, Commander 7 Sector Brigadier Dharam Raj Rai said the analysis of weapons and other items revered from five militants killing in gunfight in upper reaches of Rafiabad suggest that the group belonged to Lashkar-e-Toiba. He said four AK-47 rifles, one pistol and other 

### 76950 <|endoftext|>The Ranji Trophy series which is been commencing from 2019 December, had Bengal Vs Delhi in the Eden Garden, Kolkata on 27th January 2020. Bengal batted the first innings where Delhi won the toss and decided to field, A Raman and KB Gosh opened for the team. Raman left the ground with 9(19) runs by the Delhi bowlers and the left-handed batsman Kazi Saifi was replaced. Gosh scored 46(122) runs until Jonty Sidhu took the batsman wicket. Manoj Tiwary who is the vice-captain of the Beng

### 81027 uador’s president has lashed out at WikiLeaks founder Julian Assange even as he says his government is working behind the scenes to help him out of the Ecuadorean embassy in London. Lenin Moreno said in a televised interview Sunday that Assange had become “more than a nuisance” after he violated terms of his asylum by interfering in other countries’ political affairs. In an earlier interview, Moreno said that Assange’s “poor hygiene and housekeeping habits” were a continuing distraction to embas

### 82269 Hill 303 massacre |Hill 303 massacre| Bodies of massacre victims gathered near Waegwan, South Korea, many with their hands still bound |Location||Hill 303, Waegwan, South Korea| |Date||August 17, 1950 |Target||U.S. Army prisoners of war| |Deaths||42 prisoners executed| |4–5 prisoners wounded| |Perpetrators||North Korean army soldiers| The Hill 303 massacre (Korean: 303 고지 학살 사건) was a war crime that took place during the Korean War on August 17, 1950, on a hill above Waegwan, South Korea. Forty-

### 88237 <|endoftext|>Public Member Functions |deterministic phase in radians | |void||resetEnvelopes (const Breakpoint &bp, double srate)| |void||setPhase (double ph)| |void||oscillate (double *begin, double *end, const Breakpoint &bp, double srate)| |double||amplitude (void) const| |Return the instantaneous amplitde of the Oscillator. | |double||bandwidth (void) const| |Return the instantaneous bandwidth of the Oscillator. | |double||phase (void) const| |Return the instantaneous phase of the Oscillator

### 90040  2014<|endoftext|>The defense in the court-martial of U.S. Army Pfc. Bradley Manning rested its case Wednesday after just three days and ten witnesses. The prosecution, by contrast, took five weeks to present its case against Private Manning, as they pursued charges including "aiding the enemy," which could carry the death penalty, though the prosecution is seeking "only" a life sentence in military custody with no parole. But defense lawyer David Coombs revealed in court that according to testi

### 94043 ….<|endoftext|>Kingdom of Mauretania, presen-day Algeria & Morocco. Influenced Roman Empire [225 BC] The Kingdom of Mauretania was founded in the third century BC, approximately 225 BC. According to modern ethnic taxonomies, its inhabitants are of Berber descent, and it is today located in the western region of Algeria and Northern Morocco. Mauretania was a kingdom ruled by the Mauri Peoples, who would go on to become famous in history. The Phoenicians gave the region the name Mauharim, which me

### 94695 ian Assange: Costs of policing Wikileaks founder reach £10m - 6 February 2015 - From the section UK Scotland Yard has spent about £10m providing a 24-hour guard at the Ecuadorean embassy in London since Wikileaks founder Julian Assange claimed asylum there, figures show. Mr Assange, who denies allegations he sexually assaulted two women in Sweden, faces arrest if he leaves the embassy. A Wikileaks spokesman said the policing costs were "embarrassing". Deputy Prime Minister Nick Clegg said Mr Ass

### 94933 Stockholm: Sweden said it did not agree with a UN panel which ruled Friday that WikiLeaks founder Julian Assange's stay in Ecuador's London embassy amounted to "unlawful detention". "The government does not agree with the assessment made by the majority of the Working Group," the foreign ministry said in a letter to the panel, adding that the body does not have the right to "interfere in an ongoing case handled by a Swedish public authority". Swedish authorities issued a pan-European warrant in 

### 97014 't Modi govt buy 7 squadrons of Rafale jets, asks Chidambaram New Delhi, Dec 15: In a sarcastic jibe at the Union Government, senior Congress leader P Chidambaram asked why the BJP-led government did not buy seven squadrons of Rafale jets if it had negotiated them for a lesser price than UPA. In a series of tweets, Chidambaram said Jaitley has been maintaining that in the Rafale deal, negotiated by the NDA government, the price of the aircraft was cheaper by 9 per cent or 20 per cent. Former uni

### 97673  President Barack Obama says the time has come for Syrian President Bashar Assad to resign for the sake of his brutally repressed people. In a stinging written statement, Obama said Assad has overseen a vicious onslaught of his people as they protest for freedoms. He said the Syrian people will decide their country’s future, but Assad is standing in their way and must go. Obama said Assad’s calls for reform ring hollow while he is “imprisoning, torturing and slaughtering his own people.” This wa

### 100352  by [...]<|endoftext|>|Born||Theni, Tamil Nadu, India| |Died||18 April 2008| Theni Kunjarammal (died 18 April 2008) was an Indian actress and playback singer who has worked in the Tamil film industry. As a playback singer, she has worked extensively with A. R. Rahman during the late 1990s and early 2000s for folk songs, while also regularly collaborating with Harris Jayaraj. As an actress, Kunjarammal is best known for her roles as an old woman in a rural village, and made a breakthrough with he

### 100668 height<|endoftext|>Assange to address United Nations WikiLeaks founder Julian Assange is due to make a speech to the United Nations on the eve of the 100th day since he sought political asylum at the Ecuadorian embassy in London. Mr Assange will speak to a UN meeting in New York over a satellite link. He arrived at the embassy on June 19 as part of his bid to avoid extradition to Sweden where he faces sex allegations. Mr Assange fears he will be extradited to the United States over the activitie

### 102696  Chief age row: PM meets Antony Against the backdrop of the age controversy of Army Chief V K Singh, PM Manmohan Singh held a half hour meeting with Defence Minister A K Antony. New Delhi: Against the backdrop of the age controversy of Army Chief V K Singh, Prime Minister Manmohan Singh on Wednesday held a half hour one-to-one meeting with Defence Minister A K Antony here. The Prime Minister and Antony held discussions after the Cabinet Committee on Security (CCS) meeting got over, fuelling spec

### 105294 <|endoftext|>- Afghanistan - David Petraeus - hostages - kidnapping - UK Petraeus launches investigation into death of British hostage US General David Petraeus launched an investigation Monday into the death of a British hostage in Afghanistan amid claims she may have been killed by a grenade detonated by her rescuers and not by her kidnappers. AFP - US General David Petraeus on Monday ordered an investigation into the death of a British hostage, saying it was not possible to determine conclusi

### 108673 Here are the list of players included in each of the eight playing team in IPL 2007-08. The tournament will begin on April 18, when Bangalore takes on Kolkata at the Chinnaswamy Stadium in Bangalore. The tournament will feature 59 matches in total, the teams playing each other on a home-and-away basis and top four teams will qualify for the semifinal round. 1st and 2nd Semi Final will be played on 30th and 31st of May 2008. Final of IPL will be played on 1st of June 2008 in Mumbai. Bangalore Roy

### 114704 Attendees | All Canada Games Register Here Accommodations Select Page Recruits Attending &lt;br /&gt;&lt;br /&gt; Recruits will receive a link after registration to get listed as an attendee. Recruits with an existing ConnectLAX profile can simply click “Attend Event” while logged in to join. Colleges Attending &lt;br /&gt;&lt;br /&gt; Director Login WordPress Themes

### 121191  Conditions<|endoftext|>1st Battalion, 26th Infantry Regiment  Subscribe Now ! Sign In Sign Out Home :: Military :: Agencies :: Army :: FORSCOM :: 1st Infantry Division :: 3rd Brigade Combat Team :: SITREP Military Menu Introduction Systems Facilities Agencies Industry Operations Countries Hot Documents News Reports Policy Budget Congress Links WMD Intelligence Homeland Security Space Public Eye Military Further Reading Units Organic HHC "Wolfpack" A Company "Apache" B Company "Bushmasters" C

### 123985 <|endoftext|>Cast range - Dota 2 Wiki Gamepedia Help Sign In Register Cast range From Dota 2 Wiki Jump to:	navigation, search Play By the forge of creation. This section is under construction. It may still lack crucial information or contain unvalidated statements. You can help by coordinating with the authors and offer your help. Cast range is the range at which a hero may use an ability on another unit. Cast range can be extended by certain abilities and talents. Contents 1 List of cast ranges

### 124196 Journal of English Language Studies Journal Content Search Search Scope All Authors Title Abstract Index terms Full Text Browse By Issue By Author By Title Other Journals Categories Notifications View Subscribe User Username Password Remember me QUICK MENU Focus & Scope Publication Ethics Editorial Team Peer Reviewers Author Guidelines Indexing Online Submission Peer Review Proccess Screening for Plagiarism ISSN BARCODE TEMPLATE VISITORS Home About Login Register Categories Search Current Archiv

### 133508  Zini<|endoftext|>Drukair gets new aircraft « Gumar Adventures border-bottom:0;width:200px;margin:0;padding:0}div.searchbox-form{margin:5px 10px 5px 10px}div.horbar1,div.horbar2{font-size:1px;clear:both;display:block;position:relative;padding:0;margin:0;width:100%;}div.horbar1{height:2px;background:#ffffff;border-top:dashed 1px #cccccc}div.horbar2{height:5px;background:#ffffff;border-bottom:dashed 1px #cccccc}div.header-image-container{position:relative;margin:0;padding:0;height:250px;}div.click

### 137360 Attendees | All Canada Games Register Here Accommodations Select Page Recruits Attending &lt;br /&gt;&lt;br /&gt; Recruits will receive a link after registration to get listed as an attendee. Recruits with an existing ConnectLAX profile can simply click “Attend Event” while logged in to join. Colleges Attending &lt;br /&gt;&lt;br /&gt; Director Login WordPress Themes

### 143847  Conditions<|endoftext|>1st Battalion, 26th Infantry Regiment  Subscribe Now ! Sign In Sign Out Home :: Military :: Agencies :: Army :: FORSCOM :: 1st Infantry Division :: 3rd Brigade Combat Team :: SITREP Military Menu Introduction Systems Facilities Agencies Industry Operations Countries Hot Documents News Reports Policy Budget Congress Links WMD Intelligence Homeland Security Space Public Eye Military Further Reading Units Organic HHC "Wolfpack" A Company "Apache" B Company "Bushmasters" C

### 146641 <|endoftext|>Cast range - Dota 2 Wiki Gamepedia Help Sign In Register Cast range From Dota 2 Wiki Jump to:	navigation, search Play By the forge of creation. This section is under construction. It may still lack crucial information or contain unvalidated statements. You can help by coordinating with the authors and offer your help. Cast range is the range at which a hero may use an ability on another unit. Cast range can be extended by certain abilities and talents. Contents 1 List of cast ranges

### 146852 're OK to continue.<|endoftext|>Register Journal of English Language Studies Journal Content Search Search Scope All Authors Title Abstract Index terms Full Text Browse By Issue By Author By Title Other Journals Categories Notifications View Subscribe User Username Password Remember me QUICK MENU Focus & Scope Publication Ethics Editorial Team Peer Reviewers Author Guidelines Indexing Online Submission Peer Review Proccess Screening for Plagiarism ISSN BARCODE TEMPLATE VISITORS Home About Login 

### 156164  gets new aircraft « Gumar Adventures border-bottom:0;width:200px;margin:0;padding:0}div.searchbox-form{margin:5px 10px 5px 10px}div.horbar1,div.horbar2{font-size:1px;clear:both;display:block;position:relative;padding:0;margin:0;width:100%;}div.horbar1{height:2px;background:#ffffff;border-top:dashed 1px #cccccc}div.horbar2{height:5px;background:#ffffff;border-bottom:dashed 1px #cccccc}div.header-image-container{position:relative;margin:0;padding:0;height:250px;}div.clickable{position:absolute;to

### 163002  gPowered byeMuseum<|endoftext|>Instantiate Java Way2Java a blog for Java Responsive Menu Home Table Of Contents Search Instantiate Java Java General Instantiate Java S. Nageswara Rao, Corporate Trainer August 18, 2013 2 Comments In Java, object creation is known as instantiation because an instance of a class is object. Let us explain more through Instantiate Java. Java public class Demo { public static void main(String args[]) { Demo d1 = new Demo(); } } 1 2 3 4 5 6 7 public class Demo { publi

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### 179651  All Rights Reserved.<|endoftext|>麻将技巧大全:淘宝在线装修模板：简约通用190宽淘宝左侧装修模板 - HOME-麻将 ? 麻将 搜索 鱼摆摆网，助力广大电商网店卖家创业成功！ 麻将 电商资讯 装修模板 卖家教程 微商|网店货源 创业经验 卖家问答 电商视频 卖家工具 作图大师 当前位置 麻将 > 装修模板 > 190像素宽模板 > 淘宝在线装修模板：简约通用190宽淘宝左侧装修模板 栏目：190像素宽模板 ??时间：2016-07-17 23:44 麻将 www.hm7y.com.cn 分享一个淘宝左侧190自定义?？榘沧笆褂玫奶员υ谙?a href='//www.hm7y.com.cn/html/' target='_blank'>装修模板：简约通用190宽淘宝左侧装修模板，模板中背景色、?？楸晏馔?、宝贝图、宝贝标题、价格、链接均可以在线设置操作，然后快速制作淘宝装修模板。另外，模板中可以自由添加、删除显示的宝贝数量，一般不超过20个宝贝。 模板里我们默认放的是女装类宝贝主图

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experiments/global.json 182016
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HELDOUT_PPL 322.945  loss 5.7775  train_s 54  /tmp/dev_train.npy
(dev PPL on multi_dev; official uses a hidden disjoint sample of the same HQ domain)

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  232       09:14  0.0 node /usr/bin/codex exec --dangerously-bypass-approvals-and-sandbox --skip-git-repo-check --model azure_ai/gpt-5.6-sol --json --enable unified_exec -c model_reasoning_effort=high -c model_reasoning_effort=high -c request_max_retries=12 -c stream_max_retries=12 -c stream_idle_timeout_ms=600000 -- # Task: Curate a raw web corpus to train the best small language model  ## Context You are assembling the pretraining data for a small language model. You have a large pool of **raw web documents** at `/workspace/data/pool.jsonl` — one JSON object per line: `{"id": <int>, "text": "..."}`. The documents are unlabeled. The pool holds **182,016 documents (~200M GPT-2 tokens total)**.  Compute is fixed: the model is trained on a **fixed budget of 12,000,000 tokens** — only ~6% of the pool, far smaller than the whole thing. So you cannot train on everything: you must decide *which* documents are worth training on. The training pipeline tokenizes your selection (GPT-2 BPE) in priority order and stops once it has accumulated 12M tokens.  ## Goal Curate the pool: choose the documents that, trained on under the fixed budget, produce the **best language model**. Quality is measured by **held-out perplexity on a BROAD, multi-domain high-quality English target** — equal parts encyclopedic (Wikipedia), general high-quality web prose, news, and technical Q&A. This is your disclosed target: select data that makes the model good across *all* of these registers, not just one. Lower perplexity is better.  ## Deliverables 1. `/workspace/submission/selection.json` — a JSON list of pool `id`s to train    on, in **priority order** (best first). The training pipeline consumes your    list in order until the **12M-token** budget is filled, then trains. Provide    enough ids to cover at least 12M tokens (a few hundred MB of text is ample);    ids beyond the budget are simply unused. 2. `/workspace/submission/curate.py` — the reproducible script that produced    your selection from a stated criterion (not a hand-picked id list). 3. `/workspace/claim.md` — Hypothesis / Mechanism (predict an observable other    than the final perplexity) / Falsification / Transfer.  ## Resources - The **frozen training script** is provided (`/workspace/train_nano.py`, with   `model.py`). It trains a ~30M-parameter GPT from scratch on a token budget with   fixed hyperparameters. **You may run it to evaluate a candidate selection**   against a dev target (`/workspace/data/multi_dev.npy`) — one run is ~60s on the   GPU — but you **cannot change it**; the official run uses an identical frozen   copy. The only thing you control is the data selection. - Standard GPU sandbox (Python, PyTorch, transformers). How you assess document   quality is entirely up to you (filters, classifiers, heuristics, a model, etc.). - Your session ends when the wall-clock budget runs out — check   `/workspace/.timer/remaining_secs` at any point for the authoritative time left   (don't assume a fixed number of hours). Every training run you do comes out of   that budget. - No internet. The pool's documents are freshly assembled; you cannot look up   any quality labels — any quality signal must come from your own analysis.  ## How you are scored Official: your selection fills the fixed token budget, the frozen script trains the 30M GPT from scratch, and the verifier measures the **absolute held-out perplexity on the hidden high-quality target** (a different sample from the disclosed domain than the dev set). That perplexity is your score. **Lower is better** — the goal is simply to push held-out perplexity as low as you can.  The verifier reports the raw perplexity and does no normalization. For reference and for a separate downstream normalization step, the benchmark records two fixed anchors: a **baseline** of held-out perplexity from a random selection (the do-nothing reference), and a **theoretical best** of perplexity 1 (the perplexity floor, unreachable in practice). Aim to get your held-out perplexity well below the random baseline.  ## Constraints - `selection.json` must be produced by `curate.py` from a stated criterion; an   opaque hand-picked id list fails the publishability check even if it scores well. - A selection with duplicate or out-of-range ids, or too few tokens to fill the   budget, is marked invalid (no score recorded) and excluded from ranking, so it   can't win and doesn't distort averages. 
  240       09:14  2.4 /usr/lib/node_modules/@openai/codex/node_modules/@openai/codex-linux-x64/vendor/x86_64-unknown-linux-musl/bin/codex exec --dangerously-bypass-approvals-and-sandbox --skip-git-repo-check --model azure_ai/gpt-5.6-sol --json --enable unified_exec -c model_reasoning_effort=high -c model_reasoning_effort=high -c request_max_retries=12 -c stream_max_retries=12 -c stream_idle_timeout_ms=600000 -- # Task: Curate a raw web corpus to train the best small language model  ## Context You are assembling the pretraining data for a small language model. You have a large pool of **raw web documents** at `/workspace/data/pool.jsonl` — one JSON object per line: `{"id": <int>, "text": "..."}`. The documents are unlabeled. The pool holds **182,016 documents (~200M GPT-2 tokens total)**.  Compute is fixed: the model is trained on a **fixed budget of 12,000,000 tokens** — only ~6% of the pool, far smaller than the whole thing. So you cannot train on everything: you must decide *which* documents are worth training on. The training pipeline tokenizes your selection (GPT-2 BPE) in priority order and stops once it has accumulated 12M tokens.  ## Goal Curate the pool: choose the documents that, trained on under the fixed budget, produce the **best language model**. Quality is measured by **held-out perplexity on a BROAD, multi-domain high-quality English target** — equal parts encyclopedic (Wikipedia), general high-quality web prose, news, and technical Q&A. This is your disclosed target: select data that makes the model good across *all* of these registers, not just one. Lower perplexity is better.  ## Deliverables 1. `/workspace/submission/selection.json` — a JSON list of pool `id`s to train    on, in **priority order** (best first). The training pipeline consumes your    list in order until the **12M-token** budget is filled, then trains. Provide    enough ids to cover at least 12M tokens (a few hundred MB of text is ample);    ids beyond the budget are simply unused. 2. `/workspace/submission/curate.py` — the reproducible script that produced    your selection from a stated criterion (not a hand-picked id list). 3. `/workspace/claim.md` — Hypothesis / Mechanism (predict an observable other    than the final perplexity) / Falsification / Transfer.  ## Resources - The **frozen training script** is provided (`/workspace/train_nano.py`, with   `model.py`). It trains a ~30M-parameter GPT from scratch on a token budget with   fixed hyperparameters. **You may run it to evaluate a candidate selection**   against a dev target (`/workspace/data/multi_dev.npy`) — one run is ~60s on the   GPU — but you **cannot change it**; the official run uses an identical frozen   copy. The only thing you control is the data selection. - Standard GPU sandbox (Python, PyTorch, transformers). How you assess document   quality is entirely up to you (filters, classifiers, heuristics, a model, etc.). - Your session ends when the wall-clock budget runs out — check   `/workspace/.timer/remaining_secs` at any point for the authoritative time left   (don't assume a fixed number of hours). Every training run you do comes out of   that budget. - No internet. The pool's documents are freshly assembled; you cannot look up   any quality labels — any quality signal must come from your own analysis.  ## How you are scored Official: your selection fills the fixed token budget, the frozen script trains the 30M GPT from scratch, and the verifier measures the **absolute held-out perplexity on the hidden high-quality target** (a different sample from the disclosed domain than the dev set). That perplexity is your score. **Lower is better** — the goal is simply to push held-out perplexity as low as you can.  The verifier reports the raw perplexity and does no normalization. For reference and for a separate downstream normalization step, the benchmark records two fixed anchors: a **baseline** of held-out perplexity from a random selection (the do-nothing reference), and a **theoretical best** of perplexity 1 (the perplexity floor, unreachable in practice). Aim to get your held-out perplexity well below the random baseline.  ## Constraints - `selection.json` must be produced by `curate.py` from a stated criterion; an   opaque hand-picked id list fails the publishability check even if it scores well. - A selection with duplicate or out-of-range ids, or too few tokens to fill the   budget, is marked invalid (no score recorded) and excluded from ranking, so it   can't win and doesn't distort averages. 
 1426       00:36  0.2 /bin/bash -c python - <<'PY' import json,re,hashlib,collections h=collections.defaultdict(list) for line in open('data/pool.jsonl'):  d=json.loads(line); s=re.sub(r'\W+',' ',d['text'].lower()).strip(); h[hashlib.blake2b(s.encode(),digest_size=8).digest()].append(d['id']) print('unique',len(h),'dups',sum(len(v)-1 for v in h.values()),'groups',sum(len(v)>1 for v in h.values()),'max',max(map(len,h.values()))) print([v for v in h.values() if len(v)>1][:20]) PY
 1427       00:36 92.2 python -
 1473       00:01  239 python3 train_nano.py --train_npy /tmp/dev_train.npy --heldout_npy /workspace/data/multi_dev.npy --out_json /tmp/dev.json --max_iters 3000 --seed 1337