Text Generation
PEFT
Safetensors
German
English
gemma
unsloth
lora
tool-calling
memory-agent
german
synthetic-data
conversational
Instructions to use classicgrey/gemma4-e4b-memory-policy-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use classicgrey/gemma4-e4b-memory-policy-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-4-e4b-it-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "classicgrey/gemma4-e4b-memory-policy-lora") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from classicgrey/gemma4-e4b-memory-policy-lora: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/classicgrey/gemma4-e4b-memory-policy-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://classicgrey/gemma4-e4b-memory-policy-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/classicgrey/gemma4-e4b-memory-policy-lora/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- d6990ce7f75130d74d394c6f428446b6f555482a33c9e5637027af47b98c46a8
- Size of remote file:
- 32.2 MB
- SHA256:
- b1d8bced9d66859cd2c3f4dcd8ab427197d4d46af3d9598b72af9fcf80b8392e
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