You can deploy this model and start earning money today!

tensorblock/
internlm2_5-7b-chat-1m-GGUF

Name: internlm2_5-7b-chat-1m-GGUF
Availability: InStock

Views

No views yet

internlm/internlm2_5-7b-chat-1m - GGUF

This repo contains GGUF format model files for internlm/internlm2_5-7b-chat-1m.

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

Forge
Forge Project
An OpenAI-compatible multi-provider routing layer.
🚀 Try it now! 🚀
Awesome MCP Servers	TensorBlock Studio
MCP Servers	Studio
A comprehensive collection of Model Context Protocol (MCP) servers.	A lightweight, open, and extensible multi-LLM interaction studio.
👀 See what we built 👀	👀 See what we built 👀

## Prompt template

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

Filename	Quant type	File Size	Description
internlm2_5-7b-chat-1m-Q2_K.gguf	Q2_K	2.799 GB	smallest, significant quality loss - not recommended for most purposes
internlm2_5-7b-chat-1m-Q3_K_S.gguf	Q3_K_S	3.237 GB	very small, high quality loss
internlm2_5-7b-chat-1m-Q3_K_M.gguf	Q3_K_M	3.567 GB	very small, high quality loss
internlm2_5-7b-chat-1m-Q3_K_L.gguf	Q3_K_L	3.850 GB	small, substantial quality loss
internlm2_5-7b-chat-1m-Q4_0.gguf	Q4_0	4.147 GB	legacy; small, very high quality loss - prefer using Q3_K_M
internlm2_5-7b-chat-1m-Q4_K_S.gguf	Q4_K_S	4.177 GB	small, greater quality loss
internlm2_5-7b-chat-1m-Q4_K_M.gguf	Q4_K_M	4.389 GB	medium, balanced quality - recommended
internlm2_5-7b-chat-1m-Q5_0.gguf	Q5_0	5.004 GB	legacy; medium, balanced quality - prefer using Q4_K_M
internlm2_5-7b-chat-1m-Q5_K_S.gguf	Q5_K_S	5.004 GB	large, low quality loss - recommended
internlm2_5-7b-chat-1m-Q5_K_M.gguf	Q5_K_M	5.129 GB	large, very low quality loss - recommended
internlm2_5-7b-chat-1m-Q6_K.gguf	Q6_K	5.914 GB	very large, extremely low quality loss
internlm2_5-7b-chat-1m-Q8_0.gguf	Q8_0	7.659 GB	very large, extremely low quality loss - not recommended

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_5-7b-chat-1m-GGUF --include "internlm2_5-7b-chat-1m-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_5-7b-chat-1m-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'