Hugging Face's logo

tensorblock
/
blossom-v4-mistral-7b-GGUF

GGUF
Chinese
English
TensorBlock
GGUF
Inference Endpoints
Model card Files Community
blossom-v4-mistral-7b-GGUF / README.md
morriszms's picture
morriszms
Upload folder using huggingface_hub
cf7886b verified
preview code
|
raw
history blame contribute delete
4.95 kB
metadata
license: apache-2.0
datasets:
  - Azure99/blossom-chat-v2
  - Azure99/blossom-math-v3
  - Azure99/blossom-wizard-v2
  - Azure99/blossom-orca-v2
language:
  - zh
  - en
base_model: Azure99/blossom-v4-mistral-7b
tags:
  - TensorBlock
  - GGUF
TensorBlock

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

Azure99/blossom-v4-mistral-7b - GGUF

This repo contains GGUF format model files for Azure99/blossom-v4-mistral-7b.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Prompt template

Model file specification

Filename Quant type File Size Description
blossom-v4-mistral-7b-Q2_K.gguf Q2_K 2.719 GB smallest, significant quality loss - not recommended for most purposes
blossom-v4-mistral-7b-Q3_K_S.gguf Q3_K_S 3.165 GB very small, high quality loss
blossom-v4-mistral-7b-Q3_K_M.gguf Q3_K_M 3.519 GB very small, high quality loss
blossom-v4-mistral-7b-Q3_K_L.gguf Q3_K_L 3.822 GB small, substantial quality loss
blossom-v4-mistral-7b-Q4_0.gguf Q4_0 4.109 GB legacy; small, very high quality loss - prefer using Q3_K_M
blossom-v4-mistral-7b-Q4_K_S.gguf Q4_K_S 4.140 GB small, greater quality loss
blossom-v4-mistral-7b-Q4_K_M.gguf Q4_K_M 4.368 GB medium, balanced quality - recommended
blossom-v4-mistral-7b-Q5_0.gguf Q5_0 4.998 GB legacy; medium, balanced quality - prefer using Q4_K_M
blossom-v4-mistral-7b-Q5_K_S.gguf Q5_K_S 4.998 GB large, low quality loss - recommended
blossom-v4-mistral-7b-Q5_K_M.gguf Q5_K_M 5.131 GB large, very low quality loss - recommended
blossom-v4-mistral-7b-Q6_K.gguf Q6_K 5.942 GB very large, extremely low quality loss
blossom-v4-mistral-7b-Q8_0.gguf Q8_0 7.696 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/blossom-v4-mistral-7b-GGUF --include "blossom-v4-mistral-7b-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/blossom-v4-mistral-7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'