Instructions to use Felladrin/gguf-TinyMistral-248M-Chat-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Felladrin/gguf-TinyMistral-248M-Chat-v2 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 Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Felladrin/gguf-TinyMistral-248M-Chat-v2: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 Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Felladrin/gguf-TinyMistral-248M-Chat-v2: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 Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M

Use Docker

docker model run hf.co/Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M

LM Studio
Jan
Ollama
How to use Felladrin/gguf-TinyMistral-248M-Chat-v2 with Ollama:
```
ollama run hf.co/Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M
```

Unsloth Studio

How to use Felladrin/gguf-TinyMistral-248M-Chat-v2 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Felladrin/gguf-TinyMistral-248M-Chat-v2 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Felladrin/gguf-TinyMistral-248M-Chat-v2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Felladrin/gguf-TinyMistral-248M-Chat-v2 to start chatting

Docker Model Runner
How to use Felladrin/gguf-TinyMistral-248M-Chat-v2 with Docker Model Runner:
```
docker model run hf.co/Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M
```

Lemonade

How to use Felladrin/gguf-TinyMistral-248M-Chat-v2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Felladrin/gguf-TinyMistral-248M-Chat-v2:Q4_K_M

Run and chat with the model

lemonade run user.gguf-TinyMistral-248M-Chat-v2-Q4_K_M

List all available models

lemonade list

Atomic Chat

GGUF version of Felladrin/TinyMistral-248M-Chat-v2.

Try it with llama.cpp

brew install ggerganov/ggerganov/llama.cpp

llama-cli \
  --hf-repo Felladrin/gguf-TinyMistral-248M-Chat-v2 \
  --model TinyMistral-248M-Chat-v2.Q8_0.gguf \
  --random-prompt \
  --temp 1.3 \
  --dynatemp-range 1.2 \
  --top-k 0 \
  --top-p 1 \
  --min-p 0.1 \
  --typical 0.85 \
  --mirostat 2 \
  --mirostat-ent 3.5 \
  --repeat-penalty 1.1 \
  --repeat-last-n -1 \
  -n 256

Downloads last month: 44

GGUF

Model size

0.2B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for Felladrin/gguf-TinyMistral-248M-Chat-v2

Base model

Locutusque/TinyMistral-248M

Finetuned

Felladrin/TinyMistral-248M-Chat-v4

Quantized

(16)

this model