Instructions to use MohammedNasser/silma_9b_instruct_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MohammedNasser/silma_9b_instruct_ft 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="MohammedNasser/silma_9b_instruct_ft")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MohammedNasser/silma_9b_instruct_ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MohammedNasser/silma_9b_instruct_ft: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/MohammedNasser/silma_9b_instruct_ft/resolve/main/tokenizer.json
- Command line
-
hf download hf://MohammedNasser/silma_9b_instruct_ft/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MohammedNasser/silma_9b_instruct_ft/resolve/main/tokenizer.json
17.5 MB
- Xet hash:
- 2240111495d671e3d25f7faadf64a800da0814535cf6bbc9250f4aee782d92a9
- Size of remote file:
- 17.5 MB
- SHA256:
- 3b4284b6710dbe0a8b11ce7dd969f4f8ba9c48239d59482e25b803db7feeaefc
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