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:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("darshjoshi16/phi2-lora-math", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f43d0b2ef8d48b06ea4f71d16c6067b29e90da0047f048408eab170d6e1c863f
- Size of remote file:
- 36.7 MB
- SHA256:
- 2ea9e0bb91d0a655322955c4a6f3d1be9512f16e68a2b843f4d193d13d5c13d2
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