Instructions to use dewdev/Doge-60M-Instruct-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dewdev/Doge-60M-Instruct-ONNX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="dewdev/Doge-60M-Instruct-ONNX", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("dewdev/Doge-60M-Instruct-ONNX", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("dewdev/Doge-60M-Instruct-ONNX", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- a606e36bcadb14bf1bd08f9672cccfe7c23db6aec4845ba7ba0572509825ed83
- Size of remote file:
- 169 kB
- SHA256:
- 848a831bbe3d91b2de514552805c73ef652a3100e0fbc7f5c20cedaadabba2e7
路
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