Instructions to use eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-random-GemmaForCausalLM") model = PeftModel.from_pretrained(base_model, "eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095: direct link, hf CLI and curl.
- Browser
- Download file 34.3 MB
-
https://huggingface.co/eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095/resolve/main/tokenizer.json
- Command line
-
hf download hf://eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095/resolve/main/tokenizer.json
34.3 MB
- Xet hash:
- a1f3e8de7d03ad1056f0b7e3e9d70794841d0bfb2f712a3d0b42109de434c9cd
- Size of remote file:
- 34.3 MB
- SHA256:
- a63c485bbbab0efcfc1ffe32fd177108a9f70be1875ea3aacad3c4f064a5974b
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