Text Generation
Transformers
PyTorch
TensorFlow
JAX
French
gpt2
Eval Results (legacy)
text-generation-inference
Instructions to use asi/gpt-fr-cased-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asi/gpt-fr-cased-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="asi/gpt-fr-cased-base")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("asi/gpt-fr-cased-base") model = AutoModelForCausalLM.from_pretrained("asi/gpt-fr-cased-base") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use asi/gpt-fr-cased-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "asi/gpt-fr-cased-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "asi/gpt-fr-cased-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/asi/gpt-fr-cased-base
- SGLang
How to use asi/gpt-fr-cased-base 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 "asi/gpt-fr-cased-base" \ --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": "asi/gpt-fr-cased-base", "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 "asi/gpt-fr-cased-base" \ --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": "asi/gpt-fr-cased-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use asi/gpt-fr-cased-base with Docker Model Runner:
docker model run hf.co/asi/gpt-fr-cased-base
use_cache set to False in config
#1
by eliolio - opened
Hi π
Many thanks for sharing the model!
Is there a reason why the use_cache parameter is set to false in this model config? I noticed that the model was quite slow in inference and setting use_cache to True did speed up the forward pass.
Also, this parameter is not specified in the gpt-fr-cased-small version.
Hi eliolio, thanks for the update proposition. I changed the parameter value to true as you suggested since there's no particular reason for it.
asi changed discussion status to closed