Text Classification
Transformers
PyTorch
bert
Generated from Trainer
sibyl
Eval Results (legacy)
text-embeddings-inference
Instructions to use fabriceyhc/bert-base-uncased-amazon_polarity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fabriceyhc/bert-base-uncased-amazon_polarity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fabriceyhc/bert-base-uncased-amazon_polarity")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fabriceyhc/bert-base-uncased-amazon_polarity") model = AutoModelForSequenceClassification.from_pretrained("fabriceyhc/bert-base-uncased-amazon_polarity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fabriceyhc/bert-base-uncased-amazon_polarity: direct link, hf CLI and curl.
- Browser
- Download file 2.61 kB
-
https://huggingface.co/fabriceyhc/bert-base-uncased-amazon_polarity/resolve/main/training_args.bin
- Command line
-
hf download hf://fabriceyhc/bert-base-uncased-amazon_polarity/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fabriceyhc/bert-base-uncased-amazon_polarity/resolve/main/training_args.bin
2.61 kB
- Xet hash:
- 88aa0abc85ad1bffd20eb9d32158c079cdd04f40ded0933d8e8e11fd529c5ca2
- Size of remote file:
- 2.61 kB
- SHA256:
- 963f327b156517d39125ea1e010d1dd247108f6f16a2555726f1cceb7a992532
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