Text Generation
Transformers
PyTorch
Safetensors
French
gopu
feature-extraction
transformer
mixture-of-experts
Mixture of Experts
french
custom-architecture
conversational
custom_code
Instructions to use Mauricio-100/locgi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mauricio-100/locgi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Mauricio-100/locgi", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Mauricio-100/locgi", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Mauricio-100/locgi with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Mauricio-100/locgi" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mauricio-100/locgi", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Mauricio-100/locgi
- SGLang
How to use Mauricio-100/locgi 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 "Mauricio-100/locgi" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mauricio-100/locgi", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "Mauricio-100/locgi" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mauricio-100/locgi", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Mauricio-100/locgi with Docker Model Runner:
docker model run hf.co/Mauricio-100/locgi
Upload vocab.json with huggingface_hub
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{"\n": 0, " ": 1, "%": 2, "'": 3, ",": 4, "-": 5, ".": 6, "/": 7, "0": 8, "1": 9, "2": 10, "3": 11, "4": 12, "5": 13, "6": 14, "7": 15, "8": 16, "9": 17, ":": 18, "=": 19, "?": 20, "A": 21, "B": 22, "C": 23, "D": 24, "E": 25, "F": 26, "G": 27, "H": 28, "I": 29, "J": 30, "K": 31, "L": 32, "M": 33, "N": 34, "O": 35, "P": 36, "Q": 37, "R": 38, "S": 39, "T": 40, "U": 41, "V": 42, "W": 43, "X": 44, "Y": 45, "Z": 46, "a": 47, "b": 48, "c": 49, "d": 50, "e": 51, "f": 52, "g": 53, "h": 54, "i": 55, "j": 56, "k": 57, "l": 58, "m": 59, "n": 60, "o": 61, "p": 62, "q": 63, "r": 64, "s": 65, "t": 66, "u": 67, "v": 68, "w": 69, "x": 70, "y": 71, "z": 72, "\u00b0": 73, "\u00b2": 74, "\u00c9": 75, "\u00d7": 76, "\u00e0": 77, "\u00e1": 78, "\u00e2": 79, "\u00e7": 80, "\u00e8": 81, "\u00e9": 82, "\u00ea": 83, "\u00eb": 84, "\u00ed": 85, "\u00ee": 86, "\u00ef": 87, "\u00f3": 88, "\u00f4": 89, "\u00f9": 90, "\u00fb": 91, "\u014d": 92, "\u0153": 93}
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