Text Generation
Transformers
Safetensors
Spanish
gpt2
chatbot
conversational
text-generation-inference
Instructions to use ostorc/Conversational_Spanish_GPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ostorc/Conversational_Spanish_GPT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ostorc/Conversational_Spanish_GPT") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ostorc/Conversational_Spanish_GPT") model = AutoModelForCausalLM.from_pretrained("ostorc/Conversational_Spanish_GPT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ostorc/Conversational_Spanish_GPT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ostorc/Conversational_Spanish_GPT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ostorc/Conversational_Spanish_GPT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ostorc/Conversational_Spanish_GPT
- SGLang
How to use ostorc/Conversational_Spanish_GPT 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 "ostorc/Conversational_Spanish_GPT" \ --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": "ostorc/Conversational_Spanish_GPT", "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 "ostorc/Conversational_Spanish_GPT" \ --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": "ostorc/Conversational_Spanish_GPT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ostorc/Conversational_Spanish_GPT with Docker Model Runner:
docker model run hf.co/ostorc/Conversational_Spanish_GPT
- Xet hash:
- 8560ea37b4f9fcdb02d8a15e1e77f5d11f91d3946fc578a65f524e81868f4512
- Size of remote file:
- 1.78 kB
- SHA256:
- b94b98ccb9f41e177a534698eefad4d3fd731753d10e35d81dd43a093307ff70
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