Instructions to use linyi/e3-xbch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linyi/e3-xbch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="linyi/e3-xbch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("linyi/e3-xbch") model = AutoModel.from_pretrained("linyi/e3-xbch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from linyi/e3-xbch: direct link, hf CLI and curl.
- Browser
- Download file 1.18 GB
-
https://huggingface.co/linyi/e3-xbch/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://linyi/e3-xbch/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/linyi/e3-xbch/resolve/main/pytorch_model.bin
1.18 GB
- Xet hash:
- 0f5d762cdd2b1779ec27080b85bfaf5a7c0105f9723941bb2f2123c1fe9e6ef3
- Size of remote file:
- 1.18 GB
- SHA256:
- 771317d103e9874f19ebf52e07e1506ffd34c088db39635f19fbbc886e2ce032
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