Instructions to use ajtaltarabukin2022/704b9953-dc7e-4dac-8809-b2fbb1339964 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ajtaltarabukin2022/704b9953-dc7e-4dac-8809-b2fbb1339964 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-1.5-9B-Chat-16K") model = PeftModel.from_pretrained(base_model, "ajtaltarabukin2022/704b9953-dc7e-4dac-8809-b2fbb1339964") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ajtaltarabukin2022/704b9953-dc7e-4dac-8809-b2fbb1339964: direct link, hf CLI and curl.
- Browser
- Download file 6.81 MB
-
https://huggingface.co/ajtaltarabukin2022/704b9953-dc7e-4dac-8809-b2fbb1339964/resolve/main/tokenizer.json
- Command line
-
hf download hf://ajtaltarabukin2022/704b9953-dc7e-4dac-8809-b2fbb1339964/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ajtaltarabukin2022/704b9953-dc7e-4dac-8809-b2fbb1339964/resolve/main/tokenizer.json
6.81 MB
File too large to display, you can check the raw version instead.