Text Generation
Transformers
PyTorch
Safetensors
Portuguese
llama
LLM
Portuguese
Llama 2
Eval Results (legacy)
text-generation-inference
Instructions to use dominguesm/Canarim-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dominguesm/Canarim-7B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dominguesm/Canarim-7B-Instruct")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("dominguesm/Canarim-7B-Instruct") model = AutoModelForCausalLM.from_pretrained("dominguesm/Canarim-7B-Instruct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dominguesm/Canarim-7B-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dominguesm/Canarim-7B-Instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dominguesm/Canarim-7B-Instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dominguesm/Canarim-7B-Instruct
- SGLang
How to use dominguesm/Canarim-7B-Instruct 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 "dominguesm/Canarim-7B-Instruct" \ --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": "dominguesm/Canarim-7B-Instruct", "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 "dominguesm/Canarim-7B-Instruct" \ --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": "dominguesm/Canarim-7B-Instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dominguesm/Canarim-7B-Instruct with Docker Model Runner:
docker model run hf.co/dominguesm/Canarim-7B-Instruct
Commit History
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Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (ee85e1dc6fa60f46859b49414932fc7b720bbf6a) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>738e089
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Adding the Open Portuguese LLM Leaderboard Evaluation Results (#1)
Verified signature- Adding the Open Portuguese LLM Leaderboard Evaluation Results (899003d0138b2d37ccaf9a1954ba8b766722239f) - Fixing some errors of the leaderboard evaluation results in the ModelCard yaml (bc5b8a3f949b51ad6cd681ceaf2de906bc861c38) Co-authored-by: Open PT LLM Leaderboard PR Bot <leaderboard-pt-pr-bot@users.noreply.huggingface.co>4dc8fd2
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Update README.md
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initial commit
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