TensorBlock

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

Intel/neural-chat-7b-v3-1 - GGUF

This repo contains GGUF format model files for Intel/neural-chat-7b-v3-1.

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

Prompt template

### System:
{system_prompt}
### User:
{prompt} 
### Assistant:

Model file specification

Filename Quant type File Size Description
neural-chat-7b-v3-1-Q2_K.gguf Q2_K 2.532 GB smallest, significant quality loss - not recommended for most purposes
neural-chat-7b-v3-1-Q3_K_S.gguf Q3_K_S 2.947 GB very small, high quality loss
neural-chat-7b-v3-1-Q3_K_M.gguf Q3_K_M 3.277 GB very small, high quality loss
neural-chat-7b-v3-1-Q3_K_L.gguf Q3_K_L 3.560 GB small, substantial quality loss
neural-chat-7b-v3-1-Q4_0.gguf Q4_0 3.827 GB legacy; small, very high quality loss - prefer using Q3_K_M
neural-chat-7b-v3-1-Q4_K_S.gguf Q4_K_S 3.856 GB small, greater quality loss
neural-chat-7b-v3-1-Q4_K_M.gguf Q4_K_M 4.068 GB medium, balanced quality - recommended
neural-chat-7b-v3-1-Q5_0.gguf Q5_0 4.654 GB legacy; medium, balanced quality - prefer using Q4_K_M
neural-chat-7b-v3-1-Q5_K_S.gguf Q5_K_S 4.654 GB large, low quality loss - recommended
neural-chat-7b-v3-1-Q5_K_M.gguf Q5_K_M 4.779 GB large, very low quality loss - recommended
neural-chat-7b-v3-1-Q6_K.gguf Q6_K 5.534 GB very large, extremely low quality loss
neural-chat-7b-v3-1-Q8_0.gguf Q8_0 7.167 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/neural-chat-7b-v3-1-GGUF --include "neural-chat-7b-v3-1-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/neural-chat-7b-v3-1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
92
GGUF
Model size
7.24B params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Examples
Unable to determine this model's library. Check the docs .

Model tree for tensorblock/neural-chat-7b-v3-1-GGUF

Quantized
(8)
this model

Dataset used to train tensorblock/neural-chat-7b-v3-1-GGUF

Evaluation results