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:
- 5c2fc93c8bcf03d37d1b6443fe4c7ca19e4bd753e482cd4bc9f012f01ccdd933
- Size of remote file:
- 5.3 kB
- SHA256:
- 785b405c79436261f173aa212c49c128b4078b80b4a2c0761d01be6afbc17c1c
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