Instructions to use kweston/git-base-pokemon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kweston/git-base-pokemon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="kweston/git-base-pokemon")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("kweston/git-base-pokemon") model = AutoModelForImageTextToText.from_pretrained("kweston/git-base-pokemon") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use kweston/git-base-pokemon with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kweston/git-base-pokemon" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kweston/git-base-pokemon", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/kweston/git-base-pokemon
- SGLang
How to use kweston/git-base-pokemon 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 "kweston/git-base-pokemon" \ --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": "kweston/git-base-pokemon", "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 "kweston/git-base-pokemon" \ --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": "kweston/git-base-pokemon", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use kweston/git-base-pokemon with Docker Model Runner:
docker model run hf.co/kweston/git-base-pokemon
End of training
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README.md
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Wer Score: 1.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Wer Score |
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### Framework versions
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7051
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- Wer Score: 1.6596
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Wer Score |
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| 0.7017 | 10.0 | 50 | 0.5906 | 1.7247 |
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| 0.2858 | 20.0 | 100 | 0.6435 | 1.6259 |
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| 0.1529 | 30.0 | 150 | 0.6878 | 1.7054 |
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| 0.0987 | 40.0 | 200 | 0.7051 | 1.6596 |
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### Framework versions
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model.safetensors
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