Instructions to use ulas742/lora-mid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ulas742/lora-mid 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, "ulas742/lora-mid") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1000/optimizer.pt from ulas742/lora-mid: direct link, hf CLI and curl.
- Browser
- Download file 85.3 MB
-
https://huggingface.co/ulas742/lora-mid/resolve/main/checkpoint-1000/optimizer.pt
- Command line
-
hf download hf://ulas742/lora-mid/checkpoint-1000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ulas742/lora-mid/resolve/main/checkpoint-1000/optimizer.pt
85.3 MB
- Xet hash:
- 88ca6518148fe7733a00fa1c23ec41239bfc59670ecd464d9f11a794202ada48
- Size of remote file:
- 85.3 MB
- SHA256:
- 9fd0ce7d70a53ae3909d0c467c4826aec34950fd7e48a3a7f51cf7a022d9bf11
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