Instructions to use MightyOctopus/pricer-lora-ft-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MightyOctopus/pricer-lora-ft-v3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("MightyOctopus/pricer-merged-model-A-v1") model = PeftModel.from_pretrained(base_model, "MightyOctopus/pricer-lora-ft-v3") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from MightyOctopus/pricer-lora-ft-v3: direct link, hf CLI and curl.
- Browser
- Download file 218 MB
-
https://huggingface.co/MightyOctopus/pricer-lora-ft-v3/resolve/main/optimizer.pt
- Command line
-
hf download hf://MightyOctopus/pricer-lora-ft-v3/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/MightyOctopus/pricer-lora-ft-v3/resolve/main/optimizer.pt
218 MB
- Xet hash:
- 8eb7bd371597b698d63df1a31259373e55d94d2c9d1e1e895f95c35fd9fb3eff
- Size of remote file:
- 218 MB
- SHA256:
- 7b6d76fd3321f46a51f36947a15b1c9bee754a0a789a245916692ef5d16e3264
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.