LucasFMartins commited on
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Upload fine-tuned model from Gemma Garage (request: 43a3a2fd-ada0-40f1-9a29-9f4050d94bcf)

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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ language: en
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+ license: apache-2.0
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+ tags:
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+ - fine-tuned
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+ - gemma
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+ - lora
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+ - gemma-garage
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+ base_model: google/gemma-3-1b-pt
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # test-inference
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+
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+ Fine-tuned google/gemma-3-1b-pt model from Gemma Garage
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+
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+ This model was fine-tuned using [Gemma Garage](https://github.com/your-repo/gemma-garage), a platform for fine-tuning Gemma models with LoRA.
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+
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+ ## Model Details
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+
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+ - **Base Model**: google/gemma-3-1b-pt
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+ - **Fine-tuning Method**: LoRA (Low-Rank Adaptation)
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+ - **Training Platform**: Gemma Garage
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+ - **Fine-tuned on**: 2025-07-26
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+
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+ tokenizer = AutoTokenizer.from_pretrained("LucasFMartins/test-inference")
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+ model = AutoModelForCausalLM.from_pretrained("LucasFMartins/test-inference")
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+
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+ # Generate text
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+ inputs = tokenizer("Your prompt here", return_tensors="pt")
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+ outputs = model.generate(**inputs, max_new_tokens=100)
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+ response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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+ print(response)
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+ ```
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+
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+ ## Training Details
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+
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+ This model was fine-tuned using the Gemma Garage platform with the following configuration:
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+ - Request ID: 43a3a2fd-ada0-40f1-9a29-9f4050d94bcf
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+ - Training completed on: 2025-07-26 17:53:16 UTC
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+
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+ For more information about Gemma Garage, visit [our GitHub repository](https://github.com/your-repo/gemma-garage).
added_tokens.json ADDED
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+ {
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+ "<image_soft_token>": 262144
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+ }
chat_template.jinja ADDED
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+ {{ bos_token }}
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+ {%- if messages[0]['role'] == 'system' -%}
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+ {%- if messages[0]['content'] is string -%}
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+ {%- set first_user_prefix = messages[0]['content'] + '
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+
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+ ' -%}
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+ {%- else -%}
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+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
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+
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+ ' -%}
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+ {%- endif -%}
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+ {%- set loop_messages = messages[1:] -%}
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+ {%- else -%}
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+ {%- set first_user_prefix = "" -%}
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+ {%- set loop_messages = messages -%}
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+ {%- endif -%}
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+ {%- for message in loop_messages -%}
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+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
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+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
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+ {%- endif -%}
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+ {%- if (message['role'] == 'assistant') -%}
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+ {%- set role = "model" -%}
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+ {%- else -%}
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+ {%- set role = message['role'] -%}
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+ {%- endif -%}
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+ {{ '<start_of_turn>' + role + '
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+ ' + (first_user_prefix if loop.first else "") }}
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+ {%- if message['content'] is string -%}
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+ {{ message['content'] | trim }}
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+ {%- elif message['content'] is iterable -%}
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+ {%- for item in message['content'] -%}
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+ {%- if item['type'] == 'image' -%}
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+ {{ '<start_of_image>' }}
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+ {%- elif item['type'] == 'text' -%}
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+ {{ item['text'] | trim }}
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+ {%- endif -%}
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+ {%- endfor -%}
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+ {%- else -%}
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+ {{ raise_exception("Invalid content type") }}
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+ {%- endif -%}
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+ {{ '<end_of_turn>
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+ ' }}
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+ {%- endfor -%}
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+ {%- if add_generation_prompt -%}
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+ {{ '<start_of_turn>model
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+ ' }}
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+ {%- endif -%}
config.json ADDED
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+ {
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+ "architectures": [
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+ "Gemma3ForCausalLM"
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+ ],
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+ "head_dim": 256,
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+ "hidden_activation": "gelu_pytorch_tanh",
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+ "hidden_size": 1152,
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+ "initializer_range": 0.02,
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+ "layer_types": [
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+ "sliding_attention",
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+ "bnb_4bit_quant_type": "nf4",
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+ "bnb_4bit_use_double_quant": true,
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