Instructions to use HooshvareLab/bert-fa-base-uncased-clf-digimag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-fa-base-uncased-clf-digimag with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HooshvareLab/bert-fa-base-uncased-clf-digimag")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-fa-base-uncased-clf-digimag") model = AutoModelForSequenceClassification.from_pretrained("HooshvareLab/bert-fa-base-uncased-clf-digimag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from HooshvareLab/bert-fa-base-uncased-clf-digimag: direct link, hf CLI and curl.
- Browser
- Download file 651 MB
-
https://huggingface.co/HooshvareLab/bert-fa-base-uncased-clf-digimag/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://HooshvareLab/bert-fa-base-uncased-clf-digimag/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/HooshvareLab/bert-fa-base-uncased-clf-digimag/resolve/main/flax_model.msgpack
651 MB
- Xet hash:
- adb1c8881fe9047b9bfc33f216033d999678f5dc76f77fd29800a4742170374e
- Size of remote file:
- 651 MB
- SHA256:
- 9f91e7b3ea73dd11ee41770bff06d51a4d414a18ca726ce4d55bc7f1cce618e2
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