Instructions to use Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24 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, "Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24: direct link, hf CLI and curl.
- Browser
- Download file 80 Bytes
-
https://huggingface.co/Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24/resolve/main/added_tokens.json
- Command line
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hf download hf://Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24/added_tokens.json
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curl -L -o added_tokens.json https://huggingface.co/Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24/resolve/main/added_tokens.json
80 Bytes
| { | |
| "<|endoftext|>": 151643, | |
| "<|im_end|>": 151645, | |
| "<|im_start|>": 151644 | |
| } | |