Instructions to use zhuqing/distilroberta-base-theme2-6000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhuqing/distilroberta-base-theme2-6000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="zhuqing/distilroberta-base-theme2-6000")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("zhuqing/distilroberta-base-theme2-6000") model = AutoModelForMaskedLM.from_pretrained("zhuqing/distilroberta-base-theme2-6000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zhuqing/distilroberta-base-theme2-6000: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/zhuqing/distilroberta-base-theme2-6000/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zhuqing/distilroberta-base-theme2-6000/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zhuqing/distilroberta-base-theme2-6000/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- c46fc8809533953fa8c777faec57128a7893b36b8c5046532268500ea700a9dd
- Size of remote file:
- 329 MB
- SHA256:
- c79a12a59203a473ad01f53db1f6c3a062f960a34596314cfca221968f03a2e4
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