Instructions to use vmpsergio/83ccc229-46a5-4ad6-a1b2-8f438794426e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vmpsergio/83ccc229-46a5-4ad6-a1b2-8f438794426e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "vmpsergio/83ccc229-46a5-4ad6-a1b2-8f438794426e") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from vmpsergio/83ccc229-46a5-4ad6-a1b2-8f438794426e: direct link, hf CLI and curl.
- Browser
- Download file 2.78 MB
-
https://huggingface.co/vmpsergio/83ccc229-46a5-4ad6-a1b2-8f438794426e/resolve/main/vocab.json
- Command line
-
hf download hf://vmpsergio/83ccc229-46a5-4ad6-a1b2-8f438794426e/vocab.json
-
curl -L -o vocab.json https://huggingface.co/vmpsergio/83ccc229-46a5-4ad6-a1b2-8f438794426e/resolve/main/vocab.json
2.78 MB
File too large to display, you can check the raw version instead.