Instructions to use hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9505410d4daaf83559edf820f24e4e67171199275c64d7f26ea8f3b15622dda
- Size of remote file:
- 307 kB
- SHA256:
- 4d9bea5971476fe4de1ec57998a5ca4210cf788cf82699501f99bc92a07bd2a7
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