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Haojin Yang

yanghaojin
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reacted to their post with 🔥❤️🧠🚀 9 months ago
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899
Dear community,

Please check our recent blog post, "GPU Poor Savior: Revolutionizing Low-Bit Open Source LLMs and Cost-Effective Edge Computing". A cheaper and more efficient SFT scheme for quantized LLMs is provided.

https://huggingface.co/blog/NicoNico/green-bit-llm
posted an update 9 months ago
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899
Dear community,

Please check our recent blog post, "GPU Poor Savior: Revolutionizing Low-Bit Open Source LLMs and Cost-Effective Edge Computing". A cheaper and more efficient SFT scheme for quantized LLMs is provided.

https://huggingface.co/blog/NicoNico/green-bit-llm
reacted to their post with 🚀🔥 10 months ago
replied to their post 10 months ago
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Command for reproducing this run 😉 :
CUDA_VISIBLE_DEVICES=0 WANDB_DISABLED=true python -m sft.finetune --model GreenBitAI/Llama-3-8B-layer-mix-bpw-2.2 --tune-qweight-only --galore --galore-rank 64 --optimizer adamw8bit --batch-size 1 --seqlen 96
posted an update 10 months ago
reacted to their post with 🔥 10 months ago
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1348
Dear all,

We are happy to share that we have just open-sourced over 200 low-bit LLMs. For the MLX community, we have prepared 2-4 bit versions of mainstream LLMs. You can visit the following collection to access them: GreenBitAI/greenbitai-mlx-llm-6614eb6ceb8da657c2b4ed58.

These low-bit models can be conveniently used through our open-source tool at https://github.com/GreenBitAI/gbx-lm.

Compared to other open-source quantization algorithms, these models provide better accuracy retention. We have provided some model evaluation results here:
https://github.com/GreenBitAI/green-bit-llm/blob/main/green_bit_llm/evaluation/README.md.

You can also evaluate the models yourself using the evaluation script we provided.
  • 1 reply
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posted an update 10 months ago
view post
Post
1348
Dear all,

We are happy to share that we have just open-sourced over 200 low-bit LLMs. For the MLX community, we have prepared 2-4 bit versions of mainstream LLMs. You can visit the following collection to access them: GreenBitAI/greenbitai-mlx-llm-6614eb6ceb8da657c2b4ed58.

These low-bit models can be conveniently used through our open-source tool at https://github.com/GreenBitAI/gbx-lm.

Compared to other open-source quantization algorithms, these models provide better accuracy retention. We have provided some model evaluation results here:
https://github.com/GreenBitAI/green-bit-llm/blob/main/green_bit_llm/evaluation/README.md.

You can also evaluate the models yourself using the evaluation script we provided.
  • 1 reply
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