Instructions to use darshjoshi16/phi2-lora-math with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use darshjoshi16/phi2-lora-math with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2") model = PeftModel.from_pretrained(base_model, "darshjoshi16/phi2-lora-math") - Transformers
How to use darshjoshi16/phi2-lora-math with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("darshjoshi16/phi2-lora-math", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from darshjoshi16/phi2-lora-math: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
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https://huggingface.co/darshjoshi16/phi2-lora-math/resolve/main/tokenizer.json
- Command line
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hf download hf://darshjoshi16/phi2-lora-math/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/darshjoshi16/phi2-lora-math/resolve/main/tokenizer.json
3.56 MB
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