Instructions to use Ritvik/nlp_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ritvik/nlp_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ritvik/nlp_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ritvik/nlp_model") model = AutoModelForSequenceClassification.from_pretrained("Ritvik/nlp_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Ritvik/nlp_model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Ritvik/nlp_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Ritvik/nlp_model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ritvik/nlp_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 39f8f97cf82cf9975e85038a193dbf42202e89544bdf4991b44b64789b9eceae
- Size of remote file:
- 438 MB
- SHA256:
- f06ff691354a1734515ee19e8fd7d82095c5ec2a4c98686fe64bee17c72587e3
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