Instructions to use gasolsun/DynamicRAG-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gasolsun/DynamicRAG-7B 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="gasolsun/DynamicRAG-7B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("gasolsun/DynamicRAG-7B") model = AutoModelForCausalLM.from_pretrained("gasolsun/DynamicRAG-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from gasolsun/DynamicRAG-7B: direct link, hf CLI and curl.
- Browser
- Download file 3.62 MB
-
https://huggingface.co/gasolsun/DynamicRAG-7B/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
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hf download hf://gasolsun/DynamicRAG-7B@refs/pr/2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/gasolsun/DynamicRAG-7B/resolve/refs%2Fpr%2F2/tokenizer.json
3.62 MB
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