datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1007
Retrain bank: WikiText-2 / GPT-2, random halves, seed 1007
This repository contains 100 fully retrained language models, not just scores.
Each model is GPT-2 (gpt2) fine-tuned on a different random 50% (2,328 documents)
of the 4,656-document WikiText-2 training set from
EleutherAI/bergson-wikitext-2-4656-chunks,
following the recipe of Bae et al. 2024, Training Data Attribution via Approximate
Unrolled Differentiation (App. B.1). retrained/base is trained on the full set with… See the full description on the dataset page: https://huggingface.co/datasets/EleutherAI/LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1007.LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1004
Retrain bank: WikiText-2 / GPT-2, random halves, seed 1004
This repository contains 100 fully retrained language models, not just scores.
Each model is GPT-2 (gpt2) fine-tuned on a different random 50% (2,328 documents)
of the 4,656-document WikiText-2 training set from
EleutherAI/bergson-wikitext-2-4656-chunks,
following the recipe of Bae et al. 2024, Training Data Attribution via Approximate
Unrolled Differentiation (App. B.1). retrained/base is trained on the full set with… See the full description on the dataset page: https://huggingface.co/datasets/EleutherAI/LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1004.LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1006
Retrain bank: WikiText-2 / GPT-2, random halves, seed 1006
This repository contains 100 fully retrained language models, not just scores.
Each model is GPT-2 (gpt2) fine-tuned on a different random 50% (2,328 documents)
of the 4,656-document WikiText-2 training set from
EleutherAI/bergson-wikitext-2-4656-chunks,
following the recipe of Bae et al. 2024, Training Data Attribution via Approximate
Unrolled Differentiation (App. B.1). retrained/base is trained on the full set with… See the full description on the dataset page: https://huggingface.co/datasets/EleutherAI/LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1006.LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1008
Retrain bank: WikiText-2 / GPT-2, random halves, seed 1008
This repository contains 100 fully retrained language models, not just scores.
Each model is GPT-2 (gpt2) fine-tuned on a different random 50% (2,328 documents)
of the 4,656-document WikiText-2 training set from
EleutherAI/bergson-wikitext-2-4656-chunks,
following the recipe of Bae et al. 2024, Training Data Attribution via Approximate
Unrolled Differentiation (App. B.1). retrained/base is trained on the full set with… See the full description on the dataset page: https://huggingface.co/datasets/EleutherAI/LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1008.LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1005
Retrain bank: WikiText-2 / GPT-2, random halves, seed 1005
This repository contains 100 fully retrained language models, not just scores.
Each model is GPT-2 (gpt2) fine-tuned on a different random 50% (2,328 documents)
of the 4,656-document WikiText-2 training set from
EleutherAI/bergson-wikitext-2-4656-chunks,
following the recipe of Bae et al. 2024, Training Data Attribution via Approximate
Unrolled Differentiation (App. B.1). retrained/base is trained on the full set with… See the full description on the dataset page: https://huggingface.co/datasets/EleutherAI/LDS-retrain-bank-adamw-wikitext2-N4656-bs8-seed1005.qfs-smollm2-135m-wikitext2-native-v1
HF workflow d3dc69602aeb981f06bd9f4c726937f9
A root fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-native-bf16.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-native-v1.qfs-smollm2-135m-wikitext2-gptq-g32-v1
HF workflow 32c6ab05b0ceab1cecdceda838846388
A quant fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-gptq-int4-g32.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-gptq-g32-v1.qfs-smollm2-135m-wikitext2-gptq-g64-v1
HF workflow 73f0a12a901c7368794a3a886f55b675
A quant fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-gptq-int4-g64.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-gptq-g64-v1.qfs-smollm2-135m-wikitext2-rtn-g64-v1
HF workflow ee13c03b2f256042a17c9817e17a2f20
A quant fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-rtn-int4-g64.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-rtn-g64-v1.VALUE_wikitext2_been_done
Dataset Card for "VALUE_wikitext2_been_done"
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wikitext-2-raw-v1-preprocessed-200-PP_RIP_PTP_-wikipedia-dpr-k-1-OP-False-train-perplexitywikitext-2-raw-v1-preprocessed-200-PP_RIP_PTP_-wikipedia-dpr-k-2-OP-False-train-perplexityVALUE_wikitext2_got
Dataset Card for "VALUE_wikitext2_got"
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wikitext-2-raw-v1-preprocessed-200-PP_RIP_PTP_-wikipedia-dpr-k-2-OP-True-train-perplexitywikitext-2-raw-v1-preprocessed-200-PI_KFI_-wikipedia-dpr-k-2-OP-True-train-perplexitywikitext2_VALUE
Dataset Card for "wikitext2_VALUE"
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wikitext-2-raw-v1-preprocessed-200-PI_KFI-FK_claude-train-PI_KFI_IK-perplexityVALUE_wikitext2_drop_aux
Dataset Card for "VALUE_wikitext2_drop_aux"
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VALUE_wikitext2_lexical
Dataset Card for "VALUE_wikitext2_lexical"
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wikitext-2-raw-v1-preprocessed-200-PI_KFI_-wikipedia-dpr-k-2-OP-False-train-PI_KFI-perplexitywikitext-2-raw-v1-preprocessed-200-PI_KFI-FK_-train-perplexitywikitext-2-raw-v1-preprocessed-200-PI_KFI_-wikipedia-dpr-k-1-OP-False-train-perplexityVALUE_wikitext2_negative_concord
Dataset Card for "VALUE_wikitext2_negative_concord"
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wikitext-2-raw-v1-preprocessed-200-PI_KFI_-wikipedia-dpr-k-2-OP-False-train-perplexitywikitext-2-raw-v1-preprocessed-200-PP_RIP_PTP-train-perplexityVALUE_wikitext2_dey_it
Dataset Card for "VALUE_wikitext2_dey_it"
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VALUE_wikitext2_uninflect
Dataset Card for "VALUE_wikitext2_uninflect"
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wikitext-2-raw-v1-preprocessed-200-PI_KFI_-wikipedia-dpr-k-1-OP-True-train-PI_KFI-perplexityVALUE_wikitext2_null_genetive
Dataset Card for "VALUE_wikitext2_null_genetive"
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VALUE_wikitext2_null_relcl
Dataset Card for "VALUE_wikitext2_null_relcl"
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