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 from transformers import pipeline pipe = pipeline("question-answering", model="SmallDoge/Doge-60M-Instruct", trust_remote_code=True)# 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) - Notebooks
- Google Colab
- Kaggle
Update README.md
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by JingzeShi - opened
README.md
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datasets:
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- HuggingFaceTB/smoltalk
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base_model:
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language:
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- en
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pipeline_tag: question-answering
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datasets:
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- HuggingFaceTB/smoltalk
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base_model:
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- JingzeShi/Doge-60M
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language:
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- en
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pipeline_tag: question-answering
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