Instructions to use SmallDoge/Doge-160M-Instruct-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SmallDoge/Doge-160M-Instruct-SFT 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-160M-Instruct-SFT", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SmallDoge/Doge-160M-Instruct-SFT", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("SmallDoge/Doge-160M-Instruct-SFT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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