Instructions to use siddanshchawla/m_e_c_63 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use siddanshchawla/m_e_c_63 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "siddanshchawla/m_e_c_63") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from siddanshchawla/m_e_c_63: direct link, hf CLI and curl.
- Browser
- Download file 109 MB
-
https://huggingface.co/siddanshchawla/m_e_c_63/resolve/main/optimizer.pt
- Command line
-
hf download hf://siddanshchawla/m_e_c_63/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/siddanshchawla/m_e_c_63/resolve/main/optimizer.pt
109 MB
- Xet hash:
- 5d58e83cfab31022972d3d4bede303d85106ab3e80bc932dd8f55dffdc3131fd
- Size of remote file:
- 109 MB
- SHA256:
- 27437a86ed941d5fbdecc600f04b09a5c6befd1f5301da8e2b08a1f2b141022e
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