Instructions to use minhnguyennnnnn/ab9de531-0537-4683-b5c4-903c5e8f2db9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhnguyennnnnn/ab9de531-0537-4683-b5c4-903c5e8f2db9 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "minhnguyennnnnn/ab9de531-0537-4683-b5c4-903c5e8f2db9") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from minhnguyennnnnn/ab9de531-0537-4683-b5c4-903c5e8f2db9: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/minhnguyennnnnn/ab9de531-0537-4683-b5c4-903c5e8f2db9/resolve/main/tokenizer.json
- Command line
-
hf download hf://minhnguyennnnnn/ab9de531-0537-4683-b5c4-903c5e8f2db9/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/minhnguyennnnnn/ab9de531-0537-4683-b5c4-903c5e8f2db9/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 31d19fffde1c78260dd5b32b98e51dd8adefae216e6eefbcb299f56f4b977337
- Size of remote file:
- 11.4 MB
- SHA256:
- bcfe42da0a4497e8b2b172c1f9f4ec423a46dc12907f4349c55025f670422ba9
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