datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
python-copilot-training-from-many-repos-large
Python Copilot Large Coding Dataset
This dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.
Details
Each row contains python code, either a class method or a global function, imported modules, base classes (if any), exceptions (ordered based off the code), returns (ordered based off the code), arguments (ordered based off the code), and more.
Rows: 2350782… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-copilot-training-from-many-repos-large.wikipedia_2003
Wikipedia-2003
Original dump: https://dumps.wikimedia.org/archive/2003/2003-05-16
This is a filtered and cleaned version of the 2003 Wikipedia dump.
Stats
Language
Size
Lines
Bosnian (bs)
77.6KB
78
Czech (cs)
392.8KB
354
Danish (da)
4.9MB
11,561
German (de)
23.47MB
18,490
English (en)
249MB
128,198
Esperanto (eo)
7.9MB
7,202
Spanish (es)
7.33MB
4,651
French (fr)
13.2MB
10,957
Croatian (hr)
1.2KB
3
Dutch (nl)
10.9MB
7,116
Polish (pl)… See the full description on the dataset page: https://huggingface.co/datasets/fromziro/wikipedia_2003.ChatGPT-Jailbreak-Prompts-rubend18
Dataset Card for Dataset Name
Name
ChatGPT Jailbreak Prompts
Dataset Summary
ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT.
Languages
[English]
rose_code_samples
rose_code samples (pass@8 rollouts)
vLLM pass@8 samples on the CL-From-Nothing/rose_code train split (23,688 codeforces stdin/stdout
problems), scored by the deepcoder verifier (reward=1.0 iff all test cases pass).
Qwen3-1.7B/ — student model rollouts. 23,688 questions × 8 samples = 189,504 lines.
Qwen3-4B-Thinking-2507/ — teacher model rollouts.
Sampling: temperature 0.7, top_p 0.9, max_tokens 16384, 8 samples/question (pass@8).
Each cluster file holds a contiguous… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/rose_code_samples.polaris_rose_rollouts_olmo3-7b_from_qwen3-30b-a3b_cutoff4096_240steps
Cross-tokenizer ROSE rollouts — Olmo-3-7B-Think-SFT ← Qwen3-30B-A3B-Thinking-2507
Every assembled row of a complete 240-step online-ROSE run: 61,440 rows, the teacher's
actual continuation for each, and the token accounting behind it.
The student writes a 4096-token prefix in its own vocabulary (100278). That prefix is
decoded to text, the teacher is shown it under its own chat template, and the teacher's
reply comes back as text and is tokenised into the student's vocabulary.… See the full description on the dataset page: https://huggingface.co/datasets/SeanWang0027/polaris_rose_rollouts_olmo3-7b_from_qwen3-30b-a3b_cutoff4096_240steps.RLVE-Qwen3-1.7B-Pass1-Rollouts
RLVE teacher rollouts — Qwen3-1.7B (pass@1)
Teacher rollouts for on-policy distillation on the RLVE environment suite.
Teacher / sampler: Qwen3-1.7B
Source prompts: RLVE train split — 9000 questions across RLVE-Eval Gym
environments (counting / combinatorics / optimization tasks)
Sampling: 1 sample/question (pass@1) = 9000 records,
temperature 0.7, max 4096 new tokens
Rewards: inline RLVE-Eval Gym verifier score (continuous, in [-1, 1]).
Teacher accuracy (reward>0): 20 / 9000 =… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/RLVE-Qwen3-1.7B-Pass1-Rollouts.code-eval-pass8-rollouts
Code eval (pass@8) — Qwen3 code-SFT comparison
Inference-time pass@8 rollouts on the code test split for 4 models, sampled
with eval_code_array.sbatch.
Source prompts: CL-From-Nothing/code_hard test split — 408 competitive-programming questions
Sampling: 8 samples/question (pass@8) = 3264 records/model, temperature 0.7, max_model_len 32000. Main runs use 32768 max new tokens; the base model also has a supplementary 16384-token run.
Rewards: DeepCoder code verifier — 1.0 if the… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/code-eval-pass8-rollouts.rlve_teacher_topk16_20K
RLVE Teacher Top-16 Logit Data (20K)
Teacher top-k logit sidecar data for continuation-style KD-SFT warmup
(see compute_teacher_topk_logprobs.py / KDContinuationDataset).
Each row holds, per response token, the teacher's top-16 (+ forced true token)
candidate token ids and their log-probabilities, joined to the base dataset by
row_id.
Configs
rlve_offline_20K — 20,000 rows (rlve_offline_20K_teacher_top16.parquet)
rlve_rose_20K — 20,000 rows… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/rlve_teacher_topk16_20K.code_rose_initial_1_7B_SFT_10K_rollouts_Qwen3-4B-Thinking-2507_k12_t0.7_maxtok12288
code_rose_initial_1_7B_SFT_10K — rollouts (Qwen3-4B-Thinking-2507, k=12)
Pass@k completions generated with vLLM over the prefixes in
CL-From-Nothing/code_rose_initial_1_7B_SFT_10K.
Generation config
Model
Qwen3-4B-Thinking-2507
Samples per question (k)
12
Temperature
0.7
top_p
0.9
max_tokens
12288
max_model_len
32768
Questions
7250 (index 0–7249, full split)
Total rows
87000 (7250 × 12)
Generated by complete_prefix_vllm.py… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/code_rose_initial_1_7B_SFT_10K_rollouts_Qwen3-4B-Thinking-2507_k12_t0.7_maxtok12288.nemo-grpo-weak3-from084-prompts
Nemo Weak-3 GRPO Prompt Dataset
This dataset is a clean GRPO/RLVR prompt set for the three weak Nemotron
challenge types identified after the 0.84 SDPO adapter diagnostics:
bit_manipulation, unit_conversion, and gravity.
The training rows are intentionally modeled as:
prompt x + gold answer r + verifier/reward spec
There are no source CoT traces, teacher completions, SDPO samples, RLSD
privileged traces, or eval predictions in the training split. GRPO should
sample completions… See the full description on the dataset page: https://huggingface.co/datasets/dvyomkesh/nemo-grpo-weak3-from084-prompts.rose_code-Qwen3-1.7B-Pass8-Rollouts
rose_code rollouts — Qwen3-1.7B (pass@8)
Model rollouts on the rose_code test split, for the OPD coding pipeline.
Model / sampler: Qwen3-1.7B
Source prompts: CL-From-Nothing/rose_code test split — 408 competitive-programming questions (codeforces-style)
Sampling: 8 samples/question (pass@8) = 3264 records, temperature 0.7, max 16384 new tokens, max_model_len 32000
Rewards: DeepCoder code verifier (deepcoder_reward_fn.py) — 1.0 if the generated program passes all unit tests… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/rose_code-Qwen3-1.7B-Pass8-Rollouts.RLVE-Qwen3-4B-Thinking-2507-Pass8-Rollouts
RLVE teacher rollouts — Qwen3-4B-Thinking-2507 (pass@8)
Teacher rollouts for on-policy distillation on the RLVE environment suite.
Teacher / sampler: Qwen3-4B-Thinking-2507
Source prompts: RLVE train split — 9000 questions across 18 environments
(counting / combinatorics / optimization tasks)
Sampling: 8 samples/question (pass@8) = 72000 records,
temperature 1.0 (sample.sh default 0.7 -> here T per run), max 16384 new tokens
Rewards: recomputed offline with the RLVE-Eval Gym… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/RLVE-Qwen3-4B-Thinking-2507-Pass8-Rollouts.rlve_offline_20K_POPE_prefix_pass1_qwen3-1.7b
RLVE offline-20K POPE-prefix completions — Qwen3-1.7B (pass1)
Prefix-conditioned completions generated by Qwen3-1.7B over the
rlve_offline_20K_POPE_prefix prompt set (20000 records, 1 sample/prompt).
Produced by SLURM job 6580578 (vLLM, tp=2), 2026-06-15.
Fields
index, sample_id, prompt, prefix, response, answer, rewards
⚠️ Caveat on rewards
The inline rewards field is all 0.0 — this is the known inline-Gym-verifier
artifact (same as the old… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/rlve_offline_20K_POPE_prefix_pass1_qwen3-1.7b.RLVE-Test-Qwen3-1.7B-GRPO-step70-Pass8
RLVE test eval — GRPO step70 (pass@8)
Evaluation rollouts on the RLVE test split.
Model: grpo_train_Qwen3-1.7B-SFT-rlve-20K-1epoch (GRPO, step 70)
Source prompts: RLVE test split — 180 questions (RLVE-Eval Gym environments)
Sampling: 8 samples/question (pass@8) = 1440 records, temperature 0.7,
max 16384 new tokens
Rewards: inline RLVE-Eval Gym verifier score (continuous, in [-1, 1]).
Record-level accuracy (reward>0): 216 / 1440 = 15.0%, mean reward -0.677
pass@8 (>=1 of 8… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/RLVE-Test-Qwen3-1.7B-GRPO-step70-Pass8.RLVE-Test-Qwen3-1.7B-SFT-warmup-Pass8
RLVE test eval — SFT warmup (pass@8)
Evaluation rollouts on the RLVE test split.
Model: Qwen3-1.7B-SFT-rlve-20K-1epoch (RL-warmup baseline, pre-RL)
Source prompts: RLVE test split — 180 questions (RLVE-Eval Gym environments)
Sampling: 8 samples/question (pass@8) = 1440 records, temperature 0.7,
max 16384 new tokens
Rewards: inline RLVE-Eval Gym verifier score (continuous, in [-1, 1]).
Record-level accuracy (reward>0): 176 / 1440 = 12.2%, mean reward -0.724
pass@8 (>=1 of 8… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/RLVE-Test-Qwen3-1.7B-SFT-warmup-Pass8.nemo-bit-manipulation-from084-r32-1712
Nemo Bit Manipulation SDPO/RLSD Inspection Set
This dataset is an inspection archive for the dedicated bit_manipulation continuation experiments from NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 using the post-SDPO 0.84 adapter.
The Hugging Face viewer uses stable Parquet splits:
train: one row per curated bit group.
samples: one row per rollout/teacher sample, with completion preview and tail fields.
holdout: two 0/8 groups held out because the source CoT was not verified as exact.… See the full description on the dataset page: https://huggingface.co/datasets/dvyomkesh/nemo-bit-manipulation-from084-r32-1712.