Instructions to use protagonist/gemma4-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use protagonist/gemma4-classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("protagonist/gemma4-classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use protagonist/gemma4-classification 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 protagonist/gemma4-classification 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 protagonist/gemma4-classification to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for protagonist/gemma4-classification to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="protagonist/gemma4-classification", max_seq_length=2048, )
| { | |
| "alora_invocation_tokens": null, | |
| "alpha_pattern": {}, | |
| "arrow_config": null, | |
| "auto_mapping": { | |
| "base_model_class": "Gemma4ForConditionalGeneration", | |
| "parent_library": "transformers.models.gemma4.modeling_gemma4", | |
| "unsloth_fixed": true | |
| }, | |
| "base_model_name_or_path": "unsloth/gemma-4-26B-A4B-it", | |
| "bias": "none", | |
| "corda_config": null, | |
| "ensure_weight_tying": false, | |
| "eva_config": null, | |
| "exclude_modules": null, | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 64, | |
| "lora_bias": false, | |
| "lora_dropout": 0, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "peft_version": "0.18.1", | |
| "qalora_group_size": 16, | |
| "r": 64, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "v_proj", | |
| "up_proj", | |
| "gate_proj", | |
| "down_proj", | |
| "k_proj", | |
| "q_proj", | |
| "o_proj" | |
| ], | |
| "target_parameters": [ | |
| "mlp.experts.gate_up_proj", | |
| "mlp.experts.down_proj" | |
| ], | |
| "task_type": "CAUSAL_LM", | |
| "trainable_token_indices": null, | |
| "use_dora": false, | |
| "use_qalora": false, | |
| "use_rslora": false | |
| } |