Instructions to use ParsaKgvr/mmdBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ParsaKgvr/mmdBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ParsaKgvr/mmdBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ParsaKgvr/mmdBERT") model = AutoModelForSequenceClassification.from_pretrained("ParsaKgvr/mmdBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ParsaKgvr/mmdBERT: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/ParsaKgvr/mmdBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ParsaKgvr/mmdBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ParsaKgvr/mmdBERT/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 1c303876b01ed5f8cd771a220e5585f7c85d971ca95eab0f6deb3823aa75e455
- Size of remote file:
- 433 MB
- SHA256:
- 82d8653e493165f930d780e2d6d4941f47183a14c93ee4569daaf06d2b1ea635
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