Instructions to use tavtav/mistral-test-model3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tavtav/mistral-test-model3 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="tavtav/mistral-test-model3")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tavtav/mistral-test-model3")
model = AutoModelForCausalLM.from_pretrained("tavtav/mistral-test-model3")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tavtav/mistral-test-model3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tavtav/mistral-test-model3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tavtav/mistral-test-model3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/tavtav/mistral-test-model3

SGLang

How to use tavtav/mistral-test-model3 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "tavtav/mistral-test-model3" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tavtav/mistral-test-model3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "tavtav/mistral-test-model3" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tavtav/mistral-test-model3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use tavtav/mistral-test-model3 with Docker Model Runner:
```
docker model run hf.co/tavtav/mistral-test-model3
```

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Check out the documentation for more information.

trained on fanfiction data and roleplay data

no specific format was used for the dataset. Aka, not used for alpaca or pyg format. The quality is questionable.

Downloads last month: 2

Safetensors

Model size

7B params

Tensor type

F16