Instructions to use IPG5/elastic-seq-classifier-llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use IPG5/elastic-seq-classifier-llama with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("models-pretrained/llama\\model") model = PeftModel.from_pretrained(base_model, "IPG5/elastic-seq-classifier-llama") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from IPG5/elastic-seq-classifier-llama: direct link, hf CLI and curl.
- Browser
- Download file 35.2 kB
-
https://huggingface.co/IPG5/elastic-seq-classifier-llama/resolve/main/optimizer.pt
- Command line
-
hf download hf://IPG5/elastic-seq-classifier-llama/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/IPG5/elastic-seq-classifier-llama/resolve/main/optimizer.pt
35.2 kB
- Xet hash:
- d2624efff93323a9a6a78dc3830a993a2de2db31ed8a677831aacde6b6f72a3e
- Size of remote file:
- 35.2 kB
- SHA256:
- 25392b5d183e8ca7893fbf05ca0a01af3f25b3daf7bbaa07ff384a6d836b9ff0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.