Text Generation
PEFT
Safetensors
Russian
English
gemma4
lora
reasoning
math
agent
tool-use
function-calling
multimodal
russian
unsloth
conversational
4-bit precision
bitsandbytes
Instructions to use rrchat/Cerberus-E4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rrchat/Cerberus-E4B 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, "rrchat/Cerberus-E4B") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from rrchat/Cerberus-E4B: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/rrchat/Cerberus-E4B/resolve/main/tokenizer.json
- Command line
-
hf download hf://rrchat/Cerberus-E4B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/rrchat/Cerberus-E4B/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- c62336ad134cad6f154d84eb0e5a5fa9ca17cd665ef3ba5ac4fd02b1486760b4
- Size of remote file:
- 32.2 MB
- SHA256:
- cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f
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