Instructions to use rjmacarthy/codegen-350M-finetuned-react with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rjmacarthy/codegen-350M-finetuned-react with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rjmacarthy/codegen-350M-finetuned-react")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("rjmacarthy/codegen-350M-finetuned-react") model = AutoModelForCausalLM.from_pretrained("rjmacarthy/codegen-350M-finetuned-react") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use rjmacarthy/codegen-350M-finetuned-react with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rjmacarthy/codegen-350M-finetuned-react" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rjmacarthy/codegen-350M-finetuned-react", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rjmacarthy/codegen-350M-finetuned-react
- SGLang
How to use rjmacarthy/codegen-350M-finetuned-react 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 "rjmacarthy/codegen-350M-finetuned-react" \ --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": "rjmacarthy/codegen-350M-finetuned-react", "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 "rjmacarthy/codegen-350M-finetuned-react" \ --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": "rjmacarthy/codegen-350M-finetuned-react", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rjmacarthy/codegen-350M-finetuned-react with Docker Model Runner:
docker model run hf.co/rjmacarthy/codegen-350M-finetuned-react
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README.md
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This model is a fine-tuned version of [Salesforce/codegen-350M-multi](https://huggingface.co/Salesforce/codegen-350M-multi) on the [EddieChen372/react_repos](https://huggingface.co/datasets/EddieChen372/react_repos) dataset.
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- lr_scheduler_type: linear
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- num_epochs: 1.0
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### Training results
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### Framework versions
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- Transformers 4.32.0.dev0
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This model is a fine-tuned version of [Salesforce/codegen-350M-multi](https://huggingface.co/Salesforce/codegen-350M-multi) on the [EddieChen372/react_repos](https://huggingface.co/datasets/EddieChen372/react_repos) dataset.
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### Training hyperparameters
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The following hyperparameters were used during training:
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- lr_scheduler_type: linear
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- num_epochs: 1.0
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### Framework versions
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- Transformers 4.32.0.dev0
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