Instructions to use Abdulmohsena/Faseeh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abdulmohsena/Faseeh 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="Abdulmohsena/Faseeh")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Abdulmohsena/Faseeh") model = AutoModelForSeq2SeqLM.from_pretrained("Abdulmohsena/Faseeh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Abdulmohsena/Faseeh: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/Abdulmohsena/Faseeh/resolve/main/tokenizer.json
- Command line
-
hf download hf://Abdulmohsena/Faseeh/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Abdulmohsena/Faseeh/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- eeb1e4c4bf35e4f3eb67a7d63d56b4194f0af02f1b9b1df0ed48aa6fa312e84c
- Size of remote file:
- 32.2 MB
- SHA256:
- b3be18cc91c94d4a1d83731ace4dac0b90a7db024edecdeb9fe7d19ec01ce901
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