Instructions to use unsloth/gemma-4-E4B-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Local Apps Settings
- Unsloth Studio
How to use unsloth/gemma-4-E4B-it 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 unsloth/gemma-4-E4B-it 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 unsloth/gemma-4-E4B-it to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/gemma-4-E4B-it to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="unsloth/gemma-4-E4B-it", max_seq_length=2048, )
Upload folder using huggingface_hub
Browse files- config.json +1 -1
- tokenizer_config.json +0 -1
config.json
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"vocab_size_per_layer_input": 262144
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},
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"tie_word_embeddings": true,
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"transformers_version": "5.
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"unsloth_fixed": true,
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"video_token_id": 258884,
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"vision_config": {
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"vocab_size_per_layer_input": 262144
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},
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"tie_word_embeddings": true,
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"transformers_version": "5.5.0",
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"unsloth_fixed": true,
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"video_token_id": 258884,
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"vision_config": {
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tokenizer_config.json
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],
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"image_token": "<|image|>",
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"is_local": true,
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"local_files_only": false,
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"mask_token": "<mask>",
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"model_max_length": 131072,
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"model_specific_special_tokens": {
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],
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"image_token": "<|image|>",
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"is_local": true,
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"mask_token": "<mask>",
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"model_max_length": 131072,
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"model_specific_special_tokens": {
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