Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/2-LLAMA3SP-jirasoftware with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/2-LLAMA3SP-jirasoftware with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "DEVCamiloSepulveda/2-LLAMA3SP-jirasoftware") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from DEVCamiloSepulveda/2-LLAMA3SP-jirasoftware: direct link, hf CLI and curl.
- Browser
- Download file 1.56 GB
-
https://huggingface.co/DEVCamiloSepulveda/2-LLAMA3SP-jirasoftware/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://DEVCamiloSepulveda/2-LLAMA3SP-jirasoftware/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/DEVCamiloSepulveda/2-LLAMA3SP-jirasoftware/resolve/main/pytorch_model.bin
1.56 GB
- Xet hash:
- 841f75b5a8dda719d5419bde69308a085397ddc95d916c8ad193ddb137693f9e
- Size of remote file:
- 1.56 GB
- SHA256:
- f4f3ba63e26887614fae21eca3c1e82caf7b726f9dc4f237056623535c8a8ac2
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