Instructions to use Jackkkkk/tm-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jackkkkk/tm-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Jackkkkk/tm-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Jackkkkk/tm-bert") model = AutoModel.from_pretrained("Jackkkkk/tm-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jackkkkk/tm-bert: direct link, hf CLI and curl.
- Browser
- Download file 426 MB
-
https://huggingface.co/Jackkkkk/tm-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jackkkkk/tm-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jackkkkk/tm-bert/resolve/main/pytorch_model.bin
426 MB
- Xet hash:
- a466ec1d46a02980b166d4c4c90a47f33e5a571d4663bcae7410d6b70a0a44c0
- Size of remote file:
- 426 MB
- SHA256:
- 2f5aae15c29a0d4832abc931c6d539d41e0eb4d476d494fc7f12a5bfa9a9edee
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