Instructions to use dev-analyzer/file_path_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dev-analyzer/file_path_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dev-analyzer/file_path_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dev-analyzer/file_path_model") model = AutoModelForSequenceClassification.from_pretrained("dev-analyzer/file_path_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fbf29fc95a637e0f29f489460548cc71b5a570dcd4b64549a94f2138b3ba2888
- Size of remote file:
- 438 MB
- SHA256:
- db7444ec1b9b956d6d18f9f0157d86dca945badde5679cc0d0025d9ae7cd5001
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