Instructions to use harish/PT-FalseFalse-0_2_BEST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/PT-FalseFalse-0_2_BEST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harish/PT-FalseFalse-0_2_BEST")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harish/PT-FalseFalse-0_2_BEST") model = AutoModelForSequenceClassification.from_pretrained("harish/PT-FalseFalse-0_2_BEST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from harish/PT-FalseFalse-0_2_BEST: direct link, hf CLI and curl.
- Browser
- Download file 712 MB
-
https://huggingface.co/harish/PT-FalseFalse-0_2_BEST/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://harish/PT-FalseFalse-0_2_BEST/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/harish/PT-FalseFalse-0_2_BEST/resolve/main/pytorch_model.bin
712 MB
- Xet hash:
- 8f4307dc0cda415efc3d1d5d2a80cb26d3304285f1f3b7df4062e8b04a15abb7
- Size of remote file:
- 712 MB
- SHA256:
- ecab9e73c48506cd1c006fd4caa00fed3f0e788eb05d3d4188a4952bfaa4676b
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