-
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Paper • 2309.12307 • Published • 89 -
NEFTune: Noisy Embeddings Improve Instruction Finetuning
Paper • 2310.05914 • Published • 14 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 60 -
Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon
Paper • 2401.03462 • Published • 27
Collections
Discover the best community collections!
Collections including paper arxiv:2312.15685
-
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 31 -
Tuning Language Models by Proxy
Paper • 2401.08565 • Published • 22 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 69
-
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
Paper • 2312.15685 • Published • 16 -
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
Paper • 2502.02737 • Published • 249 -
The Llama 3 Herd of Models
Paper • 2407.21783 • Published • 117
-
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 66 -
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 74 -
Your Transformer is Secretly Linear
Paper • 2405.12250 • Published • 158 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 65
-
INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning
Paper • 2401.06532 • Published • 12 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 88 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 51 -
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
Paper • 2312.15685 • Published • 16
-
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
Paper • 2312.15685 • Published • 16 -
mistralai/Mixtral-8x7B-Instruct-v0.1
47B • Updated • 409k • 4.61k -
microsoft/phi-2
Text Generation • 3B • Updated • 821k • 3.41k -
TinyLlama/TinyLlama-1.1B-Chat-v1.0
Text Generation • 1B • Updated • 2.65M • 1.46k
-
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Paper • 2309.12307 • Published • 89 -
NEFTune: Noisy Embeddings Improve Instruction Finetuning
Paper • 2310.05914 • Published • 14 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 60 -
Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon
Paper • 2401.03462 • Published • 27
-
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 66 -
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 74 -
Your Transformer is Secretly Linear
Paper • 2405.12250 • Published • 158 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 65
-
INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning
Paper • 2401.06532 • Published • 12 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 88 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 51 -
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
Paper • 2312.15685 • Published • 16
-
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 31 -
Tuning Language Models by Proxy
Paper • 2401.08565 • Published • 22 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 69
-
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
Paper • 2312.15685 • Published • 16 -
mistralai/Mixtral-8x7B-Instruct-v0.1
47B • Updated • 409k • 4.61k -
microsoft/phi-2
Text Generation • 3B • Updated • 821k • 3.41k -
TinyLlama/TinyLlama-1.1B-Chat-v1.0
Text Generation • 1B • Updated • 2.65M • 1.46k
-
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
Paper • 2312.15685 • Published • 16 -
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
Paper • 2502.02737 • Published • 249 -
The Llama 3 Herd of Models
Paper • 2407.21783 • Published • 117