Text Classification
Transformers
Safetensors
gemma4
image-text-to-text
decision-model
mixture-of-experts
vision
surogate
Instructions to use michaelfeil/rune-26b-a4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelfeil/rune-26b-a4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="michaelfeil/rune-26b-a4b")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("michaelfeil/rune-26b-a4b") model = AutoModelForMultimodalLM.from_pretrained("michaelfeil/rune-26b-a4b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from michaelfeil/rune-26b-a4b: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/michaelfeil/rune-26b-a4b/resolve/main/tokenizer.json
- Command line
-
hf download hf://michaelfeil/rune-26b-a4b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/michaelfeil/rune-26b-a4b/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- c62336ad134cad6f154d84eb0e5a5fa9ca17cd665ef3ba5ac4fd02b1486760b4
- Size of remote file:
- 32.2 MB
- SHA256:
- cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f
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