Instructions to use BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF",
	filename="tinymistral-248m-v2.5.Q4_K_M.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use BasedBots/TinyMistral-248M-v2.5-Q4_K_M-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 BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf BasedBots/TinyMistral-248M-v2.5-Q4_K_M-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 BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf BasedBots/TinyMistral-248M-v2.5-Q4_K_M-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 BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf BasedBots/TinyMistral-248M-v2.5-Q4_K_M-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 BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M
```

Unsloth Studio

How to use BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF 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 BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF 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 BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.TinyMistral-248M-v2.5-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF

This model was converted to GGUF format from Locutusque/TinyMistral-248M-v2.5 using llama.cpp. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew.

brew install ggerganov/ggerganov/llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF --model tinymistral-248m-v2.5.Q4_K_M.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF --model tinymistral-248m-v2.5.Q4_K_M.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

git clone https://github.com/ggerganov/llama.cpp &&             cd llama.cpp &&             make &&             ./main -m tinymistral-248m-v2.5.Q4_K_M.gguf -n 128

Downloads last month: 5

GGUF

Model size

0.2B params

Architecture

llama

Hardware compatibility

4-bit

Inference Providers NEW

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

Datasets used to train BasedBots/TinyMistral-248M-v2.5-Q4_K_M-GGUF

Evaluation results

normalized accuracy on AI2 Reasoning Challenge (25-Shot)
test set Open LLM Leaderboard

24.570
normalized accuracy on HellaSwag (10-Shot)
validation set Open LLM Leaderboard

27.490
accuracy on MMLU (5-Shot)
test set Open LLM Leaderboard

23.150
mc2 on TruthfulQA (0-shot)
validation set Open LLM Leaderboard

46.720
accuracy on Winogrande (5-shot)
validation set Open LLM Leaderboard

47.830
accuracy on GSM8k (5-shot)
test set Open LLM Leaderboard

0.000