Fill-Mask
Transformers
Safetensors
pinyin_code
masked-lm
trust-remote-code
sentencepiece
custom_code
Instructions to use timorobrecht/full_chinese_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use timorobrecht/full_chinese_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="timorobrecht/full_chinese_bert", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("timorobrecht/full_chinese_bert", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from timorobrecht/full_chinese_bert: direct link, hf CLI and curl.
- Browser
- Download file 285 kB
-
https://huggingface.co/timorobrecht/full_chinese_bert/resolve/main/tokenizer.model
- Command line
-
hf download hf://timorobrecht/full_chinese_bert/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/timorobrecht/full_chinese_bert/resolve/main/tokenizer.model
285 kB
- Xet hash:
- e36ddff89e9b74d4e7028b9dd136c94171f8cb2cce3215e95376697aa7396e2b
- Size of remote file:
- 285 kB
- SHA256:
- b2e974c61c600b4800e805f871c6cff97bb89c40f5a4a6e02d02f873b41692ed
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