Instructions to use SriSanthM/LLAMA-3.2-1B-MathInstrcu-LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SriSanthM/LLAMA-3.2-1B-MathInstrcu-LORA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "SriSanthM/LLAMA-3.2-1B-MathInstrcu-LORA") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-600/optimizer.pt from SriSanthM/LLAMA-3.2-1B-MathInstrcu-LORA: direct link, hf CLI and curl.
- Browser
- Download file 45.3 MB
-
https://huggingface.co/SriSanthM/LLAMA-3.2-1B-MathInstrcu-LORA/resolve/main/checkpoint-600/optimizer.pt
- Command line
-
hf download hf://SriSanthM/LLAMA-3.2-1B-MathInstrcu-LORA/checkpoint-600/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/SriSanthM/LLAMA-3.2-1B-MathInstrcu-LORA/resolve/main/checkpoint-600/optimizer.pt
45.3 MB
- Xet hash:
- 832393143d7a3264c7563fae9b0e91d8a57bbc942689e73d1da9105d753a840c
- Size of remote file:
- 45.3 MB
- SHA256:
- 35113237cc4f677cce4d3e7035cd488cb659b7941c9e437ec4cf6188004a734a
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