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
Browse files- vocab.json +1229 -1
vocab.json
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|
| 1 |
+
{
|
| 2 |
+
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| 3 |
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|
| 4 |
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|
| 5 |
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":": 3,
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| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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"?": 10,
|
| 13 |
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|
| 14 |
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|
| 15 |
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".": 13,
|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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| 20 |
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| 22 |
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| 23 |
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| 25 |
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| 26 |
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|
| 27 |
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| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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| 33 |
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|
| 34 |
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| 35 |
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| 36 |
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| 37 |
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| 95 |
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| 96 |
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| 97 |
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| 104 |
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| 113 |
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|
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}
|