Instructions to use dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dunzhang/stella_en_1.5B_v5") model = PeftModel.from_pretrained(base_model, "dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b: direct link, hf CLI and curl.
- Browser
- Download file 148 MB
-
https://huggingface.co/dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b/resolve/main/last-checkpoint/optimizer.pt
148 MB
- Xet hash:
- eb85b9937012bdf290cf7839a133ad83146aed478a015fd8c58ccd4834282aed
- Size of remote file:
- 148 MB
- SHA256:
- f51a7fc41ef0b9463b3af21795591da1bdbe2204fce56cd9cf35b0da63e29324
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