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HellaSwag

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/YingXu001/Attacks_on_Graph_Node_Attributes

공식 코드

Attacks on Node Attributes in Graph Neural Networks

https://github.com/adkipnis/metabench

공식 코드

$\texttt{metabench}$ -- A Sparse Benchmark to Measure General Ability in Large Language Models

https://github.com/allenai/rainbow

공식 코드

UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark

https://github.com/apolloresearch/gpt2_noln

공식 코드

You can remove GPT2's LayerNorm by fine-tuning

https://github.com/eternityyw/gemini-commonsense-evaluation

공식 코드

Gemini in Reasoning: Unveiling Commonsense in Multimodal Large Language Models

https://github.com/facebookresearch/layerskip

공식 코드

LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding

https://github.com/gingasan/creat

공식 코드

Toward Adversarial Training on Contextualized Language Representation

https://github.com/gkevinyen5418/LoRA-RITE

공식 코드

LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization

https://github.com/huawei-noah/kd-nlp

공식 코드

When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation

https://github.com/livnlp/prompt_bias_suppression

공식 코드

In-Contextual Gender Bias Suppression for Large Language Models

https://github.com/liyucheng09/contamination_detector

공식 코드

An Open Source Data Contamination Report for Large Language Models

https://github.com/nailashfrni/mcq-leakage-detection-code

공식 코드

Simulating Training Data Leakage in Multiple-Choice Benchmarks for LLM Evaluation

https://github.com/pchizhov/hellaswag-evaluation

공식 코드

What the HellaSwag? On the Validity of Common-Sense Reasoning Benchmarks

https://github.com/turkunlp/finerweb-10bt

공식 코드

FinerWeb-10BT: Refining Web Data with LLM-Based Line-Level Filtering

https://github.com/vnnm404/SaGE

공식 코드

SaGE: Evaluating Moral Consistency in Large Language Models

https://github.com/PlusLabNLP/Plot-guided-Coherence-Evaluation

HellaSwag: Can a Machine Really Finish Your Sentence?

https://github.com/allenai/dolma

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

https://github.com/bramiozo/PubScience

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

https://github.com/facebookresearch/text_characterization_toolkit

HellaSwag: Can a Machine Really Finish Your Sentence?

https://github.com/gair-nlp/prox

DataDecide: How to Predict Best Pretraining Data with Small Experiments

https://github.com/karpathy/llama2.c

Training Compute-Optimal Large Language Models

https://github.com/nkluge-correa/teenytinyllama

Training Compute-Optimal Large Language Models

https://github.com/rvlopes/gloria

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

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