Instructions to use Agisight/tyv-gemma4-e4b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Agisight/tyv-gemma4-e4b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-4-E4B-it") model = PeftModel.from_pretrained(base_model, "Agisight/tyv-gemma4-e4b-lora") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Agisight/tyv-gemma4-e4b-lora: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/Agisight/tyv-gemma4-e4b-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://Agisight/tyv-gemma4-e4b-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Agisight/tyv-gemma4-e4b-lora/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- e96a17bb638d7e5c417d4c2abf3cdb5af7a97b50605a250f2f6d84c29b46d1d9
- Size of remote file:
- 32.2 MB
- SHA256:
- a2619fe11b50dbed06ac443c51d757b354d0b62d64baa514404d4e84e6713519
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