Instructions to use fathyshalab/wechsel-saquad20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fathyshalab/wechsel-saquad20 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="fathyshalab/wechsel-saquad20")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("fathyshalab/wechsel-saquad20") model = AutoModelForQuestionAnswering.from_pretrained("fathyshalab/wechsel-saquad20", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from fathyshalab/wechsel-saquad20: direct link, hf CLI and curl.
- Browser
- Download file 2.22 MB
-
https://huggingface.co/fathyshalab/wechsel-saquad20/resolve/main/tokenizer.json
- Command line
-
hf download hf://fathyshalab/wechsel-saquad20/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/fathyshalab/wechsel-saquad20/resolve/main/tokenizer.json
2.22 MB
- Xet hash:
- 902434ff6d8d3c3222b01218e21883a5e52eb35f1584e00eb13fc9192d420a51
- Size of remote file:
- 2.22 MB
- SHA256:
- 5ba35fc2bdac298432ca4f9e39137c5f864d6f88515df4a9ca5099d380612433
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