Instructions to use Sara121/Ornith-1.0-9B-Engineering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sara121/Ornith-1.0-9B-Engineering 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="Sara121/Ornith-1.0-9B-Engineering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Sara121/Ornith-1.0-9B-Engineering") model = AutoModelForCausalLM.from_pretrained("Sara121/Ornith-1.0-9B-Engineering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Sara121/Ornith-1.0-9B-Engineering: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/Sara121/Ornith-1.0-9B-Engineering/resolve/main/tokenizer.json
- Command line
-
hf download hf://Sara121/Ornith-1.0-9B-Engineering/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Sara121/Ornith-1.0-9B-Engineering/resolve/main/tokenizer.json
20 MB
- Xet hash:
- 777bcaa63794fa47b8f53680be9d6d176f1fcbd7ba03cdc6c3bae2b3d76b323f
- Size of remote file:
- 20 MB
- SHA256:
- 06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
路
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