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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba80a94e18bcee14dca04ef5d7f6bc2394f1de808db9d623793ab3d93df63ff4
- Size of remote file:
- 109 MB
- SHA256:
- 13cb15b518d8602a0d9d1aab816fd00abe881a8b270f1478da39c03ee2b13bf9
路
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