Instructions to use Anudev08/model_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anudev08/model_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Anudev08/model_3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Anudev08/model_3") model = AutoModelForSequenceClassification.from_pretrained("Anudev08/model_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Anudev08/model_3: direct link, hf CLI and curl.
- Browser
- Download file 510 MB
-
https://huggingface.co/Anudev08/model_3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Anudev08/model_3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Anudev08/model_3/resolve/main/pytorch_model.bin
510 MB
- Xet hash:
- 4fc9b7f63380d1ebfc9cdd5eaa44bff4a899efacd65d044bc39a0218cbfcc18d
- Size of remote file:
- 510 MB
- SHA256:
- a4703c0b6463c6b28f077e07d521e059ef1b2ae058489c76857e4bd4d4e3fe18
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