Instructions to use ashique/BanglaTraitBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashique/BanglaTraitBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ashique/BanglaTraitBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ashique/BanglaTraitBERT") model = AutoModelForSequenceClassification.from_pretrained("ashique/BanglaTraitBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ashique/BanglaTraitBERT: direct link, hf CLI and curl.
- Browser
- Download file 1.35 GB
-
https://huggingface.co/ashique/BanglaTraitBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ashique/BanglaTraitBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ashique/BanglaTraitBERT/resolve/main/pytorch_model.bin
1.35 GB
- Xet hash:
- 4f81a67ed4ebdc65602e6373f3d2036907c63387648c47ca4b99db8565e54970
- Size of remote file:
- 1.35 GB
- SHA256:
- 02dbce424b56cd7e2a3fe9e8eab819f684a63c6096f381dee63ca572c9711c11
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