Instructions to use AvocadoMuffin/Gemma_Fine_Tuned_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AvocadoMuffin/Gemma_Fine_Tuned_Model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b-it") model = PeftModel.from_pretrained(base_model, "AvocadoMuffin/Gemma_Fine_Tuned_Model") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from AvocadoMuffin/Gemma_Fine_Tuned_Model: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/AvocadoMuffin/Gemma_Fine_Tuned_Model/resolve/main/tokenizer.json
- Command line
-
hf download hf://AvocadoMuffin/Gemma_Fine_Tuned_Model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AvocadoMuffin/Gemma_Fine_Tuned_Model/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 922b7ca7ba4d2f66d92f0b1191fe3a4010a67fe8265e9c69b1d65f60f9970339
- Size of remote file:
- 34.4 MB
- SHA256:
- f559f2189f392b4555613965f089e7c4d300b41fbe080bf79da0d676e33ee7f0
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