Instructions to use tranthaihoa/gemma_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tranthaihoa/gemma_binary with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tranthaihoa/gemma_binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
|
Download README.md from tranthaihoa/gemma_binary: direct link, hf CLI and curl.
- Browser
- Download file 580 Bytes
-
https://huggingface.co/tranthaihoa/gemma_binary/resolve/main/README.md
- Command line
-
hf download hf://tranthaihoa/gemma_binary/README.md
-
curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/tranthaihoa/gemma_binary/resolve/main/README.md
580 Bytes
metadata
base_model: unsloth/gemma-2-9b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- gemma2
- trl
Uploaded model
- Developed by: tranthaihoa
- License: apache-2.0
- Finetuned from model : unsloth/gemma-2-9b-bnb-4bit
This gemma2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
