Instructions to use Ahmed107/fasee7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmed107/fasee7 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" 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("translation", model="Ahmed107/fasee7")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ahmed107/fasee7") model = AutoModelForSeq2SeqLM.from_pretrained("Ahmed107/fasee7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ahmed107/fasee7: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Ahmed107/fasee7/resolve/main/training_args.bin
- Command line
-
hf download hf://Ahmed107/fasee7/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ahmed107/fasee7/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 91a30a249222c1f8ea43fa54a4f99042af2f645a28a8b698df401b7d9fdc8f3e
- Size of remote file:
- 4.73 kB
- SHA256:
- 4d63b9c3849e76beacf2916ae29eb9aca3a922d82246c6f2149b9f416a9e8dbc
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