Transformers
Safetensors
English
text-generation-inference
gemma4
trl
structured-output
json
function-calling
agentic-ai
Instructions to use agentbyumer/gemma4-e2b-structured-output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agentbyumer/gemma4-e2b-structured-output with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("agentbyumer/gemma4-e2b-structured-output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_config.json from agentbyumer/gemma4-e2b-structured-output: direct link, hf CLI and curl.
- Browser
- Download file 2.35 kB
-
https://huggingface.co/agentbyumer/gemma4-e2b-structured-output/resolve/main/adapter_config.json
- Command line
-
hf download hf://agentbyumer/gemma4-e2b-structured-output/adapter_config.json
-
curl -L -o adapter_config.json https://huggingface.co/agentbyumer/gemma4-e2b-structured-output/resolve/main/adapter_config.json
2.35 kB
| { | |
| "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-e2b-it-unsloth-bnb-4bit", | |
| "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": 8, | |
| "lora_bias": false, | |
| "lora_dropout": 0.0, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "peft_version": "0.18.1", | |
| "qalora_group_size": 16, | |
| "r": 8, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": "(?:(?:.*?(?:vision|image|visual|patch|language|text).*?(?:self_attn|attention|attn|mixer|mlp|feed_forward|ffn|dense|mixer).*?(?:k_proj|q_proj|v_proj|o_proj|gate_proj|up_proj|down_proj|per_layer_input_gate|per_layer_projection|linear|embedding_projection|relative_k_proj))|(?:\\bmodel\\.layers\\.[\\d]{1,}\\.(?:self_attn|attention|attn|mixer|mlp|feed_forward|ffn|dense|mixer)\\.(?:(?:k_proj|q_proj|v_proj|o_proj|gate_proj|up_proj|down_proj|per_layer_input_gate|per_layer_projection|linear|embedding_projection|relative_k_proj))))|(?:.*?\\baudio_tower\\.(?:.*\\.)?q_proj\\.linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?k_proj\\.linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?v_proj\\.linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?relative_k_proj)|(?:.*?\\baudio_tower\\.(?:.*\\.)?post\\.linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?ffw_layer_1\\.linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?ffw_layer_2\\.linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?linear_start\\.linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?linear_end\\.linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?input_proj_linear)|(?:.*?\\baudio_tower\\.(?:.*\\.)?output_proj)|(?:.*?\\bembed_audio\\.embedding_projection)|(?:.*?\\bembed_vision\\.embedding_projection)|(?:.*?\\bvision_tower\\.patch_embedder\\.input_proj)", | |
| "target_parameters": null, | |
| "task_type": "CAUSAL_LM", | |
| "trainable_token_indices": null, | |
| "use_dora": false, | |
| "use_qalora": false, | |
| "use_rslora": false | |
| } |