Instructions to use trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be/resolve/7b94404b3db61eb53fa0f8aebf30b41ccb0b0263/tokenizer.json
- Command line
-
hf download hf://trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be@7b94404b3db61eb53fa0f8aebf30b41ccb0b0263/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be/resolve/7b94404b3db61eb53fa0f8aebf30b41ccb0b0263/tokenizer.json
17.2 MB
- Xet hash:
- d1764001543899106a3168f0d55a6a527fadce55b617f89242903ae4ace0ef8d
- Size of remote file:
- 17.2 MB
- SHA256:
- 3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
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