Instructions to use nikchar/big_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikchar/big_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikchar/big_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikchar/big_model") model = AutoModelForSequenceClassification.from_pretrained("nikchar/big_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8602881dc7bf28f3acf05c10ccd4476022b4b36d2e1b918040d57a42c7f0797
- Size of remote file:
- 499 MB
- SHA256:
- b204e89200766bea9bdeb216bc069315b90bd78fa70db9abadf8c250dd58b062
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