Instructions to use nwhamed/Merged_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nwhamed/Merged_Model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nwhamed/Merged_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from nwhamed/Merged_Model: direct link, hf CLI and curl.
- Browser
- Download file 717 Bytes
-
https://huggingface.co/nwhamed/Merged_Model/resolve/main/README.md
- Command line
-
hf download hf://nwhamed/Merged_Model/README.md
-
curl -L -o README.md https://huggingface.co/nwhamed/Merged_Model/resolve/main/README.md
717 Bytes
metadata
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- google/gemma-7b
- EleutherAI/gpt-neo-2.7B
gemma_gpt
gemma_gpt is a merge of the following models using mergekit:
🧩 Configuration
"models": [
{
"model": "google/gemma-7b",
"parameters": {
"param1": "value1",
"param2": "value2"
}
},
{
"model": "EleutherAI/gpt-neo-2.7B",
"parameters": {
"param1": "value1",
"param2": "value2"
}
}
]
}