Text Generation
Transformers
PyTorch
TensorBoard
llama
Trained with AutoTrain
text-generation-inference
Instructions to use stacknexus/311fontana with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stacknexus/311fontana with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="stacknexus/311fontana")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("stacknexus/311fontana") model = AutoModelForCausalLM.from_pretrained("stacknexus/311fontana", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use stacknexus/311fontana with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "stacknexus/311fontana" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stacknexus/311fontana", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/stacknexus/311fontana
- SGLang
How to use stacknexus/311fontana 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 "stacknexus/311fontana" \ --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": "stacknexus/311fontana", "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 "stacknexus/311fontana" \ --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": "stacknexus/311fontana", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use stacknexus/311fontana with Docker Model Runner:
docker model run hf.co/stacknexus/311fontana
Download pytorch_model.bin from stacknexus/311fontana: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/stacknexus/311fontana/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://stacknexus/311fontana/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stacknexus/311fontana/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- fe03d1f7e159d95198f0e410b7af56adb7d0c3d62f283dabb7abe3033af62b1b
- Size of remote file:
- 433 MB
- SHA256:
- c30448e7d9063d3f2b05e0f106d9fe369d041c72420cd3b4b4b06433e0f1fcd2
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