Instructions to use erica/krm_sa2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erica/krm_sa2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="erica/krm_sa2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("erica/krm_sa2") model = AutoModelForSequenceClassification.from_pretrained("erica/krm_sa2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from erica/krm_sa2: direct link, hf CLI and curl.
- Browser
- Download file 406 MB
-
https://huggingface.co/erica/krm_sa2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://erica/krm_sa2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/erica/krm_sa2/resolve/main/pytorch_model.bin
406 MB
- Xet hash:
- 04fe14a026eb40d097371b43430ee7701aafd5a4e45a4a3ea6c518b4b3c7177c
- Size of remote file:
- 406 MB
- SHA256:
- e83d5f8d044683f99d4ee4e7bd2d4f724f3267c342e9761dd9762998ca6861b3
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