Instructions to use AbdullahTarek/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AbdullahTarek/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AbdullahTarek/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AbdullahTarek/results") model = AutoModelForSequenceClassification.from_pretrained("AbdullahTarek/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from AbdullahTarek/results: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/AbdullahTarek/results/resolve/main/tokenizer.json
- Command line
-
hf download hf://AbdullahTarek/results/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AbdullahTarek/results/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 6c0764d097e1fac1509be6bdfa5492fd5ecc81bd0348532fdda582bb5cd9818f
- Size of remote file:
- 17.2 MB
- SHA256:
- 76cfe2f054560aae896b2b75e273dc97a39e304d4ad19c44a9727a1d6b33c4cc
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