Instructions to use meister1378/gemma2-9b-3753_step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use meister1378/gemma2-9b-3753_step with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("meister1378/gemma2-9b-3753_step", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use meister1378/gemma2-9b-3753_step with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for meister1378/gemma2-9b-3753_step to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for meister1378/gemma2-9b-3753_step to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for meister1378/gemma2-9b-3753_step to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="meister1378/gemma2-9b-3753_step", max_seq_length=2048, )
Uploaded model
- Developed by: meister1378
- License: apache-2.0
- Finetuned from model : HumanF-MarkrAI/Gukbap-Gemma2-9B
This gemma2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Model tree for meister1378/gemma2-9b-3753_step
Base model
Markr-AI/Gukbap-Gemma2-9B