Instructions to use davidcechak/tss_bert_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidcechak/tss_bert_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="davidcechak/tss_bert_6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("davidcechak/tss_bert_6") model = AutoModel.from_pretrained("davidcechak/tss_bert_6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from davidcechak/tss_bert_6: direct link, hf CLI and curl.
- Browser
- Download file 357 MB
-
https://huggingface.co/davidcechak/tss_bert_6/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://davidcechak/tss_bert_6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/davidcechak/tss_bert_6/resolve/main/pytorch_model.bin
357 MB
- Xet hash:
- 346ffc0590fec7068b59f3751af03241028ca70548b45016e42713dde38fa475
- Size of remote file:
- 357 MB
- SHA256:
- aa658d5f573482aea003055df2e9aabe253ba2b3b199e3e98ac2607b554cc069
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