Instructions to use junjun111524/gaming_model0504 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junjun111524/gaming_model0504 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="junjun111524/gaming_model0504")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("junjun111524/gaming_model0504") model = AutoModel.from_pretrained("junjun111524/gaming_model0504", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from junjun111524/gaming_model0504: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/junjun111524/gaming_model0504/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://junjun111524/gaming_model0504/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/junjun111524/gaming_model0504/resolve/main/pytorch_model.bin
409 MB
- Xet hash:
- 6e558cc0dec5112775cb1d2375735268dcd46afc0ed9a9f3b6a161cf73bb9b89
- Size of remote file:
- 409 MB
- SHA256:
- 4e96670551ccfc1edf402ed4e8c145c46f51bbe444172611f4c93e065967c25e
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