Instructions to use DeepDream2045/0b8cf2c2-c8d1-4579-bc2a-70048db4beec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DeepDream2045/0b8cf2c2-c8d1-4579-bc2a-70048db4beec with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b") model = PeftModel.from_pretrained(base_model, "DeepDream2045/0b8cf2c2-c8d1-4579-bc2a-70048db4beec") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from DeepDream2045/0b8cf2c2-c8d1-4579-bc2a-70048db4beec: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/DeepDream2045/0b8cf2c2-c8d1-4579-bc2a-70048db4beec/resolve/main/adapter_model.bin
- Command line
-
hf download hf://DeepDream2045/0b8cf2c2-c8d1-4579-bc2a-70048db4beec/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/DeepDream2045/0b8cf2c2-c8d1-4579-bc2a-70048db4beec/resolve/main/adapter_model.bin
336 MB
- Xet hash:
- 94c738fea56cdafd7fe3832ace1f2b1ef890b64551ef422245947090691395c0
- Size of remote file:
- 336 MB
- SHA256:
- 0e1e22a7c24473ae2ce03415b098f515aeed520202a76c93116fabb734bf0b47
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.