Instructions to use silk-road/luotuo-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use silk-road/luotuo-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="silk-road/luotuo-bert", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("silk-road/luotuo-bert", trust_remote_code=True) model = AutoModel.from_pretrained("silk-road/luotuo-bert", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from silk-road/luotuo-bert: direct link, hf CLI and curl.
- Browser
- Download file 414 MB
-
https://huggingface.co/silk-road/luotuo-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://silk-road/luotuo-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/silk-road/luotuo-bert/resolve/main/pytorch_model.bin
414 MB
- Xet hash:
- 2c6393954af20081b1c71cdef06512a33c8ef2c09d346aa7f0a16dcc14248b60
- Size of remote file:
- 414 MB
- SHA256:
- a0a82772934eb24055fc3af28176176f17c78180f6c72309bc05177ef4231be7
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