Instructions to use napoler/chinese_roberta_L-2_H-512-8021 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use napoler/chinese_roberta_L-2_H-512-8021 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="napoler/chinese_roberta_L-2_H-512-8021")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("napoler/chinese_roberta_L-2_H-512-8021") model = AutoModelForMaskedLM.from_pretrained("napoler/chinese_roberta_L-2_H-512-8021", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from napoler/chinese_roberta_L-2_H-512-8021: direct link, hf CLI and curl.
- Browser
- Download file 44 MB
-
https://huggingface.co/napoler/chinese_roberta_L-2_H-512-8021/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://napoler/chinese_roberta_L-2_H-512-8021/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/napoler/chinese_roberta_L-2_H-512-8021/resolve/main/pytorch_model.bin
44 MB
- Xet hash:
- e78718d4b0c1a98c9930c508b3a5d3e7349078f898c3b39473386cb9d1f07247
- Size of remote file:
- 44 MB
- SHA256:
- 958168e83e4be77db32e4b300b9b7c0bf05e854fb359f4d2b1b0475115a5e115
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