Instructions to use tblard/tf-allocine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tblard/tf-allocine with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tblard/tf-allocine")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, TF_AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tblard/tf-allocine") model = TF_AutoModelForSequenceClassification.from_pretrained("tblard/tf-allocine", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/tblard/tf-allocine/README.md9ba1b0f
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