Instructions to use SmallDoge/Doge-60M-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SmallDoge/Doge-60M-Instruct 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="SmallDoge/Doge-60M-Instruct", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SmallDoge/Doge-60M-Instruct", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("SmallDoge/Doge-60M-Instruct", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download Doge.png from SmallDoge/Doge-60M-Instruct: direct link, hf CLI and curl.
- Browser
- Download file 169 kB
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https://huggingface.co/SmallDoge/Doge-60M-Instruct/resolve/main/Doge.png
- Command line
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hf download hf://SmallDoge/Doge-60M-Instruct/Doge.png
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curl -L -o Doge.png https://huggingface.co/SmallDoge/Doge-60M-Instruct/resolve/main/Doge.png
169 kB
