Instructions to use linyi/chirowm-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linyi/chirowm-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="linyi/chirowm-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("linyi/chirowm-large") model = AutoModelForMaskedLM.from_pretrained("linyi/chirowm-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from linyi/chirowm-large: direct link, hf CLI and curl.
- Browser
- Download file 1.3 GB
-
https://huggingface.co/linyi/chirowm-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://linyi/chirowm-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/linyi/chirowm-large/resolve/main/pytorch_model.bin
1.3 GB
- Xet hash:
- 9a6b08a537df5370cf7d25f51736a209d798de9887b736dd80eabfac4657f3b2
- Size of remote file:
- 1.3 GB
- SHA256:
- d977cf9a8a0caae728225a9d4c7cfe4a64bf018ebfc5029e79f8bd10b60d531e
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