Instructions to use bambadij/sentiment_analysis_model_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bambadij/sentiment_analysis_model_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bambadij/sentiment_analysis_model_trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bambadij/sentiment_analysis_model_trainer") model = AutoModelForSequenceClassification.from_pretrained("bambadij/sentiment_analysis_model_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bambadij/sentiment_analysis_model_trainer: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/bambadij/sentiment_analysis_model_trainer/resolve/main/training_args.bin
- Command line
-
hf download hf://bambadij/sentiment_analysis_model_trainer/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/bambadij/sentiment_analysis_model_trainer/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- eae593e194d15bc96dc93a3415547f8826a08f133fe4b8bda9a1b660637bdd98
- Size of remote file:
- 4.6 kB
- SHA256:
- 5b8c72571405080f47a8c76ae38c6cf7479385821d2ecbcc99637d580fca54da
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