metadata
license: apache-2.0
language:
- it
datasets:
- DeepMount00/gquad_it
tags:
- TensorBlock
- GGUF
base_model: DeepMount00/Minerva-3B-base-RAG
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
DeepMount00/Minerva-3B-base-RAG - GGUF
This repo contains GGUF format model files for DeepMount00/Minerva-3B-base-RAG.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
Minerva-3B-base-RAG-Q2_K.gguf | Q2_K | 1.025 GB | smallest, significant quality loss - not recommended for most purposes |
Minerva-3B-base-RAG-Q3_K_S.gguf | Q3_K_S | 1.190 GB | very small, high quality loss |
Minerva-3B-base-RAG-Q3_K_M.gguf | Q3_K_M | 1.319 GB | very small, high quality loss |
Minerva-3B-base-RAG-Q3_K_L.gguf | Q3_K_L | 1.429 GB | small, substantial quality loss |
Minerva-3B-base-RAG-Q4_0.gguf | Q4_0 | 1.538 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Minerva-3B-base-RAG-Q4_K_S.gguf | Q4_K_S | 1.549 GB | small, greater quality loss |
Minerva-3B-base-RAG-Q4_K_M.gguf | Q4_K_M | 1.632 GB | medium, balanced quality - recommended |
Minerva-3B-base-RAG-Q5_0.gguf | Q5_0 | 1.865 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Minerva-3B-base-RAG-Q5_K_S.gguf | Q5_K_S | 1.865 GB | large, low quality loss - recommended |
Minerva-3B-base-RAG-Q5_K_M.gguf | Q5_K_M | 1.913 GB | large, very low quality loss - recommended |
Minerva-3B-base-RAG-Q6_K.gguf | Q6_K | 2.212 GB | very large, extremely low quality loss |
Minerva-3B-base-RAG-Q8_0.gguf | Q8_0 | 2.865 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/Minerva-3B-base-RAG-GGUF --include "Minerva-3B-base-RAG-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/Minerva-3B-base-RAG-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'