Instructions to use Infernaught/mllama-3.2-11b-10-epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Infernaught/mllama-3.2-11b-10-epochs with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-11B-Vision") model = PeftModel.from_pretrained(base_model, "Infernaught/mllama-3.2-11b-10-epochs") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from Infernaught/mllama-3.2-11b-10-epochs: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/Infernaught/mllama-3.2-11b-10-epochs/resolve/main/rng_state.pth
- Command line
-
hf download hf://Infernaught/mllama-3.2-11b-10-epochs/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/Infernaught/mllama-3.2-11b-10-epochs/resolve/main/rng_state.pth
14.2 kB
- Xet hash:
- 6439a7858ccdcbcbc67a7c2d5db20d056ed291f7b0ef345ad04c2cf31fdb8993
- Size of remote file:
- 14.2 kB
- SHA256:
- d245e05e72192c132e0f2edb6fdcae0c578c890f0fe912f17ec7b0bba2d38cc3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.