Text Classification
Transformers
PyTorch
TensorBoard
opt
Generated from Trainer
Eval Results (legacy)
Instructions to use amosc00/NLP_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amosc00/NLP_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amosc00/NLP_sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amosc00/NLP_sentiment") model = AutoModelForSequenceClassification.from_pretrained("amosc00/NLP_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from amosc00/NLP_sentiment: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/amosc00/NLP_sentiment/resolve/main/training_args.bin
- Command line
-
hf download hf://amosc00/NLP_sentiment/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/amosc00/NLP_sentiment/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 821dfd35e07a0a609a194ef3fe7bf587f9075e0fe3e99429c87e29abdfe88a80
- Size of remote file:
- 3.52 kB
- SHA256:
- 112081d32903ba8105e2266cc14082f79f7d3e25e40b17c2c799b75a2918e61b
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