Text Classification
PEFT
Safetensors
English
gemma4
lora
multi-label-classification
text-only
research-prototype
Instructions to use mts-the-architect/open-sensations-gemma4-e2b-bf16-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mts-the-architect/open-sensations-gemma4-e2b-bf16-lora with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("google/gemma-4-E2B") model = PeftModel.from_pretrained(base_model, "mts-the-architect/open-sensations-gemma4-e2b-bf16-lora") - Notebooks
- Google Colab
- Kaggle
Download real-only-control.zip from mts-the-architect/open-sensations-gemma4-e2b-bf16-lora: direct link, hf CLI and curl.
- Browser
- Download file 10.6 MB
-
https://huggingface.co/mts-the-architect/open-sensations-gemma4-e2b-bf16-lora/resolve/main/real-only-control.zip
- Command line
-
hf download hf://mts-the-architect/open-sensations-gemma4-e2b-bf16-lora/real-only-control.zip
-
curl -L -o real-only-control.zip https://huggingface.co/mts-the-architect/open-sensations-gemma4-e2b-bf16-lora/resolve/main/real-only-control.zip
10.6 MB
- Xet hash:
- f732c1d7afa79d052156b67c847fe4d34399eaf30de60c7ed3346c99bea2a98d
- Size of remote file:
- 10.6 MB
- SHA256:
- 11e986d6e8cce487302a60add5d10375d47d189160fbcff322324e357f2d7825
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