Instructions to use QuantFactory/BioMistral-MedMNX-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/BioMistral-MedMNX-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("QuantFactory/BioMistral-MedMNX-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use QuantFactory/BioMistral-MedMNX-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/BioMistral-MedMNX-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use QuantFactory/BioMistral-MedMNX-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/BioMistral-MedMNX-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/BioMistral-MedMNX-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.BioMistral-MedMNX-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

QuantFactory/BioMistral-MedMNX-GGUF

This is quantized version of BioMistral/BioMistral-MedMNX created using llama.cpp

Original Model Card

BioMistral-MedMNX

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using johnsnowlabs/JSL-MedMNX-7B as a base.

Models Merged

The following models were included in the merge:

BioMistral/BioMistral-7B-DARE

Configuration

The following YAML configuration was used to produce this model:


models:
  - model: johnsnowlabs/JSL-MedMNX-7B
    parameters:
      density: 0.53
      weight: 0.4
  - model: BioMistral/BioMistral-7B-DARE
    parameters:
      density: 0.53
      weight: 0.3

merge_method: dare_ties
tokenizer_source: union
base_model: johnsnowlabs/JSL-MedMNX-7B
parameters:
  int8_mask: true
dtype: bfloat16

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GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

2-bit

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Base model

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Papers for QuantFactory/BioMistral-MedMNX-GGUF

Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch

Paper • 2311.03099 • Published Nov 6, 2023 • 38

Resolving Interference When Merging Models

Paper • 2306.01708 • Published Jun 2, 2023 • 19