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metadata
pipeline_tag: text-generation
license: other
tags:
  - TensorBlock
  - GGUF
base_model: internlm/internlm2-chat-7b-sft
TensorBlock

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internlm/internlm2-chat-7b-sft - GGUF

This repo contains GGUF format model files for internlm/internlm2-chat-7b-sft.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template

<s><|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
internlm2-chat-7b-sft-Q2_K.gguf Q2_K 2.799 GB smallest, significant quality loss - not recommended for most purposes
internlm2-chat-7b-sft-Q3_K_S.gguf Q3_K_S 3.237 GB very small, high quality loss
internlm2-chat-7b-sft-Q3_K_M.gguf Q3_K_M 3.567 GB very small, high quality loss
internlm2-chat-7b-sft-Q3_K_L.gguf Q3_K_L 3.850 GB small, substantial quality loss
internlm2-chat-7b-sft-Q4_0.gguf Q4_0 4.147 GB legacy; small, very high quality loss - prefer using Q3_K_M
internlm2-chat-7b-sft-Q4_K_S.gguf Q4_K_S 4.177 GB small, greater quality loss
internlm2-chat-7b-sft-Q4_K_M.gguf Q4_K_M 4.389 GB medium, balanced quality - recommended
internlm2-chat-7b-sft-Q5_0.gguf Q5_0 5.004 GB legacy; medium, balanced quality - prefer using Q4_K_M
internlm2-chat-7b-sft-Q5_K_S.gguf Q5_K_S 5.004 GB large, low quality loss - recommended
internlm2-chat-7b-sft-Q5_K_M.gguf Q5_K_M 5.129 GB large, very low quality loss - recommended
internlm2-chat-7b-sft-Q6_K.gguf Q6_K 5.914 GB very large, extremely low quality loss
internlm2-chat-7b-sft-Q8_0.gguf Q8_0 7.659 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/internlm2-chat-7b-sft-GGUF --include "internlm2-chat-7b-sft-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/internlm2-chat-7b-sft-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'