Instructions to use blackdaqlabs/Aurek with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use blackdaqlabs/Aurek with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "blackdaqlabs/Aurek") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from blackdaqlabs/Aurek: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/blackdaqlabs/Aurek/resolve/main/tokenizer.json
- Command line
-
hf download hf://blackdaqlabs/Aurek/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/blackdaqlabs/Aurek/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- f68048a2e248d9a444c7a9a1a977c674038bb759d99a51692d90f074b1a06002
- Size of remote file:
- 11.4 MB
- SHA256:
- 77aee79a8d8a7e27c91925807c684d69cf2157633fc34b9fae29e53e39dc48bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.