Instructions to use MRV1N2/Custom_GLM-4.6V-Flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MRV1N2/Custom_GLM-4.6V-Flash with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MRV1N2/Custom_GLM-4.6V-Flash", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use MRV1N2/Custom_GLM-4.6V-Flash 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 MRV1N2/Custom_GLM-4.6V-Flash 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 MRV1N2/Custom_GLM-4.6V-Flash to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MRV1N2/Custom_GLM-4.6V-Flash to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="MRV1N2/Custom_GLM-4.6V-Flash", max_seq_length=2048, )
- Xet hash:
- f50958a9a02ba453d5156d025339fde72ea6fd8dd3f007314891bf93823279db
- Size of remote file:
- 6.42 kB
- SHA256:
- a013e612bf341bb429aadfe3f19f6af23b01f9716079b6ff2659e6c41f042080
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