Instructions to use minhtrannnn/1083730b-d469-41b9-abfc-ac331f02ab97 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhtrannnn/1083730b-d469-41b9-abfc-ac331f02ab97 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Vikhrmodels/Vikhr-7B-instruct_0.4") model = PeftModel.from_pretrained(base_model, "minhtrannnn/1083730b-d469-41b9-abfc-ac331f02ab97") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from minhtrannnn/1083730b-d469-41b9-abfc-ac331f02ab97: direct link, hf CLI and curl.
- Browser
- Download file 10.2 MB
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https://huggingface.co/minhtrannnn/1083730b-d469-41b9-abfc-ac331f02ab97/resolve/main/tokenizer.json
- Command line
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hf download hf://minhtrannnn/1083730b-d469-41b9-abfc-ac331f02ab97/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/minhtrannnn/1083730b-d469-41b9-abfc-ac331f02ab97/resolve/main/tokenizer.json
10.2 MB
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