Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/7-LLAMA3SP-bamboo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/7-LLAMA3SP-bamboo 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/7-LLAMA3SP-bamboo") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from DEVCamiloSepulveda/7-LLAMA3SP-bamboo: direct link, hf CLI and curl.
- Browser
- Download file 1.56 GB
-
https://huggingface.co/DEVCamiloSepulveda/7-LLAMA3SP-bamboo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://DEVCamiloSepulveda/7-LLAMA3SP-bamboo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/DEVCamiloSepulveda/7-LLAMA3SP-bamboo/resolve/main/pytorch_model.bin
1.56 GB
- Xet hash:
- 5c3bee88804bdde69aa2d668541e0b3349dfc85746cb2b5054685c6293fdee88
- Size of remote file:
- 1.56 GB
- SHA256:
- fa19ab02e023ad51d04f2447e402b7795a5df056a3e457549399b2f546307ff6
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