Instructions to use 0x1202/1e286385-6766-46bd-b53d-c079e3d4bcb0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/1e286385-6766-46bd-b53d-c079e3d4bcb0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("The-matt/llama2_ko-7b_distinctive-snowflake-182_1060") model = PeftModel.from_pretrained(base_model, "0x1202/1e286385-6766-46bd-b53d-c079e3d4bcb0") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from 0x1202/1e286385-6766-46bd-b53d-c079e3d4bcb0: direct link, hf CLI and curl.
- Browser
- Download file 4.8 MB
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https://huggingface.co/0x1202/1e286385-6766-46bd-b53d-c079e3d4bcb0/resolve/main/tokenizer.json
- Command line
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hf download hf://0x1202/1e286385-6766-46bd-b53d-c079e3d4bcb0/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/0x1202/1e286385-6766-46bd-b53d-c079e3d4bcb0/resolve/main/tokenizer.json
4.8 MB
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