Instructions to use vanyamironov/git-base-pokemon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vanyamironov/git-base-pokemon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="vanyamironov/git-base-pokemon")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("vanyamironov/git-base-pokemon") model = AutoModelForMultimodalLM.from_pretrained("vanyamironov/git-base-pokemon", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use vanyamironov/git-base-pokemon with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vanyamironov/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": "vanyamironov/git-base-pokemon", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/vanyamironov/git-base-pokemon
- SGLang
How to use vanyamironov/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 "vanyamironov/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": "vanyamironov/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 "vanyamironov/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": "vanyamironov/git-base-pokemon", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use vanyamironov/git-base-pokemon with Docker Model Runner:
docker model run hf.co/vanyamironov/git-base-pokemon
Download training_args.bin from vanyamironov/git-base-pokemon: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/vanyamironov/git-base-pokemon/resolve/main/training_args.bin
- Command line
-
hf download hf://vanyamironov/git-base-pokemon/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/vanyamironov/git-base-pokemon/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- abc62d718c6358c5a989e0e0cf2a89138d708b68a2363eec46a4f144c6813344
- Size of remote file:
- 3.52 kB
- SHA256:
- 6bb4dc072a9c4714f5944ca19978a9badd972f6a03e876b8e74cdbcd76f23f21
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