Instructions to use Harini2506/first_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harini2506/first_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Harini2506/first_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Harini2506/first_model") model = AutoModelForTokenClassification.from_pretrained("Harini2506/first_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Harini2506/first_model: direct link, hf CLI and curl.
- Browser
- Download file 266 MB
-
https://huggingface.co/Harini2506/first_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Harini2506/first_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Harini2506/first_model/resolve/main/pytorch_model.bin
266 MB
- Xet hash:
- c2b3382debd4fcdff4a5b21f50c25b0ff332fb23e291eb927eeb2bf7b7f6a9c2
- Size of remote file:
- 266 MB
- SHA256:
- 91ada7b42a47714c29e8b24d6cd9c76ad7ff295f9c2719dce923ffa3d007f80c
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