bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1

zetlyn/models-hf model hf bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1 known 2026-10-02

https://huggingface.co/bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1

Properties

authorbofenghuang
receipt
Source
Hugging Face models
Its words
bofenghuang
Read by
field:author
Said since
2026-10-03 06:07 UTC
Last answered
2026-10-05 12:27 UTC
Original
open at the source
What the source handed over
{
  "_asked": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "_id": "6abf74c614dd63f3f6b9969c",
  "author": "bofenghuang",
  "cardData": {
    "base_model": "google/medgemma-1.5-4b-it",
    "datasets": [
      "bofenghuang/docto-decision-data-fr-v0.1"
    ],
    "language": [
      "fr"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://developers.google.com/health-ai-developer-foundations/terms",
    "license_name": "health-ai-developer-foundations",
    "tags": [
      "medical",
      "french",
      "system-one",
      "decision",
      "calibration",
      "lora"
    ]
  },
  "config": {
    "architectures": [
      "Gemma3ForConditionalGeneration"
    ],
    "chat_template_jinja": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{'<start_of_turn>model\n'}}\n{%- endif -%}\n",
    "model_type": "gemma3",
    "tokenizer_config": {
      "bos_token": "<bos>",
      "eos_token": "<eos>",
      "pad_token": "<pad>",
      "unk_token": "<unk>",
      "use_default_system_prompt": false
    }
  },
  "createdAt": "2026-10-02T09:09:26.000Z",
  "disabled": false,
  "downloads": 31,
  "gated": false,
  "id": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "lastModified": "2026-10-02T11:48:20.000Z",
  "library_name": "transformers",
  "likes": 0,
  "model-index": null,
  "modelId": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "pipeline_tag": "image-text-to-text",
  "private": false,
  "safetensors": {
    "parameters": {
      "BF16": 4300079472
    },
    "total": 4300079472
  },
  "sha": "a8701f18f698df9ecd8dd0aed61df5a21177f026",
  "siblings": [
    {
      "rfilename": ".gitattributes"
    },
    {
      "rfilename": "NOTICE"
    },
    {
      "rfilename": "README.md"
    },
    {
      "rfilename": "adapters/adapter_config.json"
    },
    {
      "rfilename": "adapters/adapter_model.safetensors"
    },
    {
      "rfilename": "assets/benchmark.png"
    },
    {
      "rfilename": "chat_template.jinja"
    },
    {
      "rfilename": "config.json"
    },
    {
      "rfilename": "generation_config.json"
    },
    {
      "rfilename": "model.safetensors"
    },
    {
      "rfilename": "preprocessor_config.json"
    },
    {
      "rfilename": "processor_config.json"
    },
    {
      "rfilename": "runs/Oct01_19-39-46_jzxh207/events.out.tfevents.1790876386.jzxh207.12069.0"
    },
    {
      "rfilename": "runs/Oct02_06-24-04_jzxh138/events.out.tfevents.1790915044.jzxh138.4191623.0"
    },
    {
      "rfilename": "special_tokens_map.json"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer.model"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [],
  "tags": [
    "transformers",
    "tensorboard",
    "safetensors",
    "gemma3",
    "image-text-to-text",
    "medical",
    "french",
    "system-one",
    "decision",
    "calibration",
    "lora",
    "conversational",
    "fr",
    "dataset:bofenghuang/docto-decision-data-fr-v0.1",
    "base_model:google/medgemma-1.5-4b-it",
    "base_model:adapter:google/medgemma-1.5-4b-it",
    "license:other",
    "text-generation-inference",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForMultimodalLM",
    "pipeline_tag": "image-text-to-text",
    "processor": "AutoProcessor"
  },
  "usedStorage": 8759321029
}
downloads31
receipt
Source
Hugging Face models
Its words
31
Read by
field:downloads
Said since
2026-10-04 12:16 UTC
Last answered
2026-10-05 12:27 UTC
Original
open at the source
2026-10-04 12:16 UTC31
2026-10-03 12:09 UTC26
2026-10-03 06:07 UTC0
What the source handed over
{
  "_asked": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "_id": "6abf74c614dd63f3f6b9969c",
  "author": "bofenghuang",
  "cardData": {
    "base_model": "google/medgemma-1.5-4b-it",
    "datasets": [
      "bofenghuang/docto-decision-data-fr-v0.1"
    ],
    "language": [
      "fr"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://developers.google.com/health-ai-developer-foundations/terms",
    "license_name": "health-ai-developer-foundations",
    "tags": [
      "medical",
      "french",
      "system-one",
      "decision",
      "calibration",
      "lora"
    ]
  },
  "config": {
    "architectures": [
      "Gemma3ForConditionalGeneration"
    ],
    "chat_template_jinja": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{'<start_of_turn>model\n'}}\n{%- endif -%}\n",
    "model_type": "gemma3",
    "tokenizer_config": {
      "bos_token": "<bos>",
      "eos_token": "<eos>",
      "pad_token": "<pad>",
      "unk_token": "<unk>",
      "use_default_system_prompt": false
    }
  },
  "createdAt": "2026-10-02T09:09:26.000Z",
  "disabled": false,
  "downloads": 31,
  "gated": false,
  "id": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "lastModified": "2026-10-02T11:48:20.000Z",
  "library_name": "transformers",
  "likes": 0,
  "model-index": null,
  "modelId": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "pipeline_tag": "image-text-to-text",
  "private": false,
  "safetensors": {
    "parameters": {
      "BF16": 4300079472
    },
    "total": 4300079472
  },
  "sha": "a8701f18f698df9ecd8dd0aed61df5a21177f026",
  "siblings": [
    {
      "rfilename": ".gitattributes"
    },
    {
      "rfilename": "NOTICE"
    },
    {
      "rfilename": "README.md"
    },
    {
      "rfilename": "adapters/adapter_config.json"
    },
    {
      "rfilename": "adapters/adapter_model.safetensors"
    },
    {
      "rfilename": "assets/benchmark.png"
    },
    {
      "rfilename": "chat_template.jinja"
    },
    {
      "rfilename": "config.json"
    },
    {
      "rfilename": "generation_config.json"
    },
    {
      "rfilename": "model.safetensors"
    },
    {
      "rfilename": "preprocessor_config.json"
    },
    {
      "rfilename": "processor_config.json"
    },
    {
      "rfilename": "runs/Oct01_19-39-46_jzxh207/events.out.tfevents.1790876386.jzxh207.12069.0"
    },
    {
      "rfilename": "runs/Oct02_06-24-04_jzxh138/events.out.tfevents.1790915044.jzxh138.4191623.0"
    },
    {
      "rfilename": "special_tokens_map.json"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer.model"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [],
  "tags": [
    "transformers",
    "tensorboard",
    "safetensors",
    "gemma3",
    "image-text-to-text",
    "medical",
    "french",
    "system-one",
    "decision",
    "calibration",
    "lora",
    "conversational",
    "fr",
    "dataset:bofenghuang/docto-decision-data-fr-v0.1",
    "base_model:google/medgemma-1.5-4b-it",
    "base_model:adapter:google/medgemma-1.5-4b-it",
    "license:other",
    "text-generation-inference",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForMultimodalLM",
    "pipeline_tag": "image-text-to-text",
    "processor": "AutoProcessor"
  },
  "usedStorage": 8759321029
}
gatedfalse
receipt
Source
Hugging Face models
Its words
false
Read by
field:gated
Said since
2026-10-03 06:07 UTC
Last answered
2026-10-05 12:27 UTC
Original
open at the source
What the source handed over
{
  "_asked": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "_id": "6abf74c614dd63f3f6b9969c",
  "author": "bofenghuang",
  "cardData": {
    "base_model": "google/medgemma-1.5-4b-it",
    "datasets": [
      "bofenghuang/docto-decision-data-fr-v0.1"
    ],
    "language": [
      "fr"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://developers.google.com/health-ai-developer-foundations/terms",
    "license_name": "health-ai-developer-foundations",
    "tags": [
      "medical",
      "french",
      "system-one",
      "decision",
      "calibration",
      "lora"
    ]
  },
  "config": {
    "architectures": [
      "Gemma3ForConditionalGeneration"
    ],
    "chat_template_jinja": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{'<start_of_turn>model\n'}}\n{%- endif -%}\n",
    "model_type": "gemma3",
    "tokenizer_config": {
      "bos_token": "<bos>",
      "eos_token": "<eos>",
      "pad_token": "<pad>",
      "unk_token": "<unk>",
      "use_default_system_prompt": false
    }
  },
  "createdAt": "2026-10-02T09:09:26.000Z",
  "disabled": false,
  "downloads": 31,
  "gated": false,
  "id": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "lastModified": "2026-10-02T11:48:20.000Z",
  "library_name": "transformers",
  "likes": 0,
  "model-index": null,
  "modelId": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "pipeline_tag": "image-text-to-text",
  "private": false,
  "safetensors": {
    "parameters": {
      "BF16": 4300079472
    },
    "total": 4300079472
  },
  "sha": "a8701f18f698df9ecd8dd0aed61df5a21177f026",
  "siblings": [
    {
      "rfilename": ".gitattributes"
    },
    {
      "rfilename": "NOTICE"
    },
    {
      "rfilename": "README.md"
    },
    {
      "rfilename": "adapters/adapter_config.json"
    },
    {
      "rfilename": "adapters/adapter_model.safetensors"
    },
    {
      "rfilename": "assets/benchmark.png"
    },
    {
      "rfilename": "chat_template.jinja"
    },
    {
      "rfilename": "config.json"
    },
    {
      "rfilename": "generation_config.json"
    },
    {
      "rfilename": "model.safetensors"
    },
    {
      "rfilename": "preprocessor_config.json"
    },
    {
      "rfilename": "processor_config.json"
    },
    {
      "rfilename": "runs/Oct01_19-39-46_jzxh207/events.out.tfevents.1790876386.jzxh207.12069.0"
    },
    {
      "rfilename": "runs/Oct02_06-24-04_jzxh138/events.out.tfevents.1790915044.jzxh138.4191623.0"
    },
    {
      "rfilename": "special_tokens_map.json"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer.model"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [],
  "tags": [
    "transformers",
    "tensorboard",
    "safetensors",
    "gemma3",
    "image-text-to-text",
    "medical",
    "french",
    "system-one",
    "decision",
    "calibration",
    "lora",
    "conversational",
    "fr",
    "dataset:bofenghuang/docto-decision-data-fr-v0.1",
    "base_model:google/medgemma-1.5-4b-it",
    "base_model:adapter:google/medgemma-1.5-4b-it",
    "license:other",
    "text-generation-inference",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForMultimodalLM",
    "pipeline_tag": "image-text-to-text",
    "processor": "AutoProcessor"
  },
  "usedStorage": 8759321029
}
licenceother
receipt
Source
Hugging Face models
Its words
other
Read by
field:cardData.license
Said since
2026-10-03 06:07 UTC
Last answered
2026-10-05 12:27 UTC
Original
open at the source
What the source handed over
{
  "_asked": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "_id": "6abf74c614dd63f3f6b9969c",
  "author": "bofenghuang",
  "cardData": {
    "base_model": "google/medgemma-1.5-4b-it",
    "datasets": [
      "bofenghuang/docto-decision-data-fr-v0.1"
    ],
    "language": [
      "fr"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://developers.google.com/health-ai-developer-foundations/terms",
    "license_name": "health-ai-developer-foundations",
    "tags": [
      "medical",
      "french",
      "system-one",
      "decision",
      "calibration",
      "lora"
    ]
  },
  "config": {
    "architectures": [
      "Gemma3ForConditionalGeneration"
    ],
    "chat_template_jinja": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{'<start_of_turn>model\n'}}\n{%- endif -%}\n",
    "model_type": "gemma3",
    "tokenizer_config": {
      "bos_token": "<bos>",
      "eos_token": "<eos>",
      "pad_token": "<pad>",
      "unk_token": "<unk>",
      "use_default_system_prompt": false
    }
  },
  "createdAt": "2026-10-02T09:09:26.000Z",
  "disabled": false,
  "downloads": 31,
  "gated": false,
  "id": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "lastModified": "2026-10-02T11:48:20.000Z",
  "library_name": "transformers",
  "likes": 0,
  "model-index": null,
  "modelId": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "pipeline_tag": "image-text-to-text",
  "private": false,
  "safetensors": {
    "parameters": {
      "BF16": 4300079472
    },
    "total": 4300079472
  },
  "sha": "a8701f18f698df9ecd8dd0aed61df5a21177f026",
  "siblings": [
    {
      "rfilename": ".gitattributes"
    },
    {
      "rfilename": "NOTICE"
    },
    {
      "rfilename": "README.md"
    },
    {
      "rfilename": "adapters/adapter_config.json"
    },
    {
      "rfilename": "adapters/adapter_model.safetensors"
    },
    {
      "rfilename": "assets/benchmark.png"
    },
    {
      "rfilename": "chat_template.jinja"
    },
    {
      "rfilename": "config.json"
    },
    {
      "rfilename": "generation_config.json"
    },
    {
      "rfilename": "model.safetensors"
    },
    {
      "rfilename": "preprocessor_config.json"
    },
    {
      "rfilename": "processor_config.json"
    },
    {
      "rfilename": "runs/Oct01_19-39-46_jzxh207/events.out.tfevents.1790876386.jzxh207.12069.0"
    },
    {
      "rfilename": "runs/Oct02_06-24-04_jzxh138/events.out.tfevents.1790915044.jzxh138.4191623.0"
    },
    {
      "rfilename": "special_tokens_map.json"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer.model"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [],
  "tags": [
    "transformers",
    "tensorboard",
    "safetensors",
    "gemma3",
    "image-text-to-text",
    "medical",
    "french",
    "system-one",
    "decision",
    "calibration",
    "lora",
    "conversational",
    "fr",
    "dataset:bofenghuang/docto-decision-data-fr-v0.1",
    "base_model:google/medgemma-1.5-4b-it",
    "base_model:adapter:google/medgemma-1.5-4b-it",
    "license:other",
    "text-generation-inference",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForMultimodalLM",
    "pipeline_tag": "image-text-to-text",
    "processor": "AutoProcessor"
  },
  "usedStorage": 8759321029
}
likes0
receipt
Source
Hugging Face models
Its words
0
Read by
field:likes
Said since
2026-10-03 06:07 UTC
Last answered
2026-10-05 12:27 UTC
Original
open at the source
What the source handed over
{
  "_asked": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "_id": "6abf74c614dd63f3f6b9969c",
  "author": "bofenghuang",
  "cardData": {
    "base_model": "google/medgemma-1.5-4b-it",
    "datasets": [
      "bofenghuang/docto-decision-data-fr-v0.1"
    ],
    "language": [
      "fr"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://developers.google.com/health-ai-developer-foundations/terms",
    "license_name": "health-ai-developer-foundations",
    "tags": [
      "medical",
      "french",
      "system-one",
      "decision",
      "calibration",
      "lora"
    ]
  },
  "config": {
    "architectures": [
      "Gemma3ForConditionalGeneration"
    ],
    "chat_template_jinja": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{'<start_of_turn>model\n'}}\n{%- endif -%}\n",
    "model_type": "gemma3",
    "tokenizer_config": {
      "bos_token": "<bos>",
      "eos_token": "<eos>",
      "pad_token": "<pad>",
      "unk_token": "<unk>",
      "use_default_system_prompt": false
    }
  },
  "createdAt": "2026-10-02T09:09:26.000Z",
  "disabled": false,
  "downloads": 31,
  "gated": false,
  "id": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "lastModified": "2026-10-02T11:48:20.000Z",
  "library_name": "transformers",
  "likes": 0,
  "model-index": null,
  "modelId": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "pipeline_tag": "image-text-to-text",
  "private": false,
  "safetensors": {
    "parameters": {
      "BF16": 4300079472
    },
    "total": 4300079472
  },
  "sha": "a8701f18f698df9ecd8dd0aed61df5a21177f026",
  "siblings": [
    {
      "rfilename": ".gitattributes"
    },
    {
      "rfilename": "NOTICE"
    },
    {
      "rfilename": "README.md"
    },
    {
      "rfilename": "adapters/adapter_config.json"
    },
    {
      "rfilename": "adapters/adapter_model.safetensors"
    },
    {
      "rfilename": "assets/benchmark.png"
    },
    {
      "rfilename": "chat_template.jinja"
    },
    {
      "rfilename": "config.json"
    },
    {
      "rfilename": "generation_config.json"
    },
    {
      "rfilename": "model.safetensors"
    },
    {
      "rfilename": "preprocessor_config.json"
    },
    {
      "rfilename": "processor_config.json"
    },
    {
      "rfilename": "runs/Oct01_19-39-46_jzxh207/events.out.tfevents.1790876386.jzxh207.12069.0"
    },
    {
      "rfilename": "runs/Oct02_06-24-04_jzxh138/events.out.tfevents.1790915044.jzxh138.4191623.0"
    },
    {
      "rfilename": "special_tokens_map.json"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer.model"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [],
  "tags": [
    "transformers",
    "tensorboard",
    "safetensors",
    "gemma3",
    "image-text-to-text",
    "medical",
    "french",
    "system-one",
    "decision",
    "calibration",
    "lora",
    "conversational",
    "fr",
    "dataset:bofenghuang/docto-decision-data-fr-v0.1",
    "base_model:google/medgemma-1.5-4b-it",
    "base_model:adapter:google/medgemma-1.5-4b-it",
    "license:other",
    "text-generation-inference",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForMultimodalLM",
    "pipeline_tag": "image-text-to-text",
    "processor": "AutoProcessor"
  },
  "usedStorage": 8759321029
}
taskimage-text-to-text
receipt
Source
Hugging Face models
Its words
image-text-to-text
Read by
field:pipeline_tag
Said since
2026-10-03 06:07 UTC
Last answered
2026-10-05 12:27 UTC
Original
open at the source
What the source handed over
{
  "_asked": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "_id": "6abf74c614dd63f3f6b9969c",
  "author": "bofenghuang",
  "cardData": {
    "base_model": "google/medgemma-1.5-4b-it",
    "datasets": [
      "bofenghuang/docto-decision-data-fr-v0.1"
    ],
    "language": [
      "fr"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://developers.google.com/health-ai-developer-foundations/terms",
    "license_name": "health-ai-developer-foundations",
    "tags": [
      "medical",
      "french",
      "system-one",
      "decision",
      "calibration",
      "lora"
    ]
  },
  "config": {
    "architectures": [
      "Gemma3ForConditionalGeneration"
    ],
    "chat_template_jinja": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{'<start_of_turn>model\n'}}\n{%- endif -%}\n",
    "model_type": "gemma3",
    "tokenizer_config": {
      "bos_token": "<bos>",
      "eos_token": "<eos>",
      "pad_token": "<pad>",
      "unk_token": "<unk>",
      "use_default_system_prompt": false
    }
  },
  "createdAt": "2026-10-02T09:09:26.000Z",
  "disabled": false,
  "downloads": 31,
  "gated": false,
  "id": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "lastModified": "2026-10-02T11:48:20.000Z",
  "library_name": "transformers",
  "likes": 0,
  "model-index": null,
  "modelId": "bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1",
  "pipeline_tag": "image-text-to-text",
  "private": false,
  "safetensors": {
    "parameters": {
      "BF16": 4300079472
    },
    "total": 4300079472
  },
  "sha": "a8701f18f698df9ecd8dd0aed61df5a21177f026",
  "siblings": [
    {
      "rfilename": ".gitattributes"
    },
    {
      "rfilename": "NOTICE"
    },
    {
      "rfilename": "README.md"
    },
    {
      "rfilename": "adapters/adapter_config.json"
    },
    {
      "rfilename": "adapters/adapter_model.safetensors"
    },
    {
      "rfilename": "assets/benchmark.png"
    },
    {
      "rfilename": "chat_template.jinja"
    },
    {
      "rfilename": "config.json"
    },
    {
      "rfilename": "generation_config.json"
    },
    {
      "rfilename": "model.safetensors"
    },
    {
      "rfilename": "preprocessor_config.json"
    },
    {
      "rfilename": "processor_config.json"
    },
    {
      "rfilename": "runs/Oct01_19-39-46_jzxh207/events.out.tfevents.1790876386.jzxh207.12069.0"
    },
    {
      "rfilename": "runs/Oct02_06-24-04_jzxh138/events.out.tfevents.1790915044.jzxh138.4191623.0"
    },
    {
      "rfilename": "special_tokens_map.json"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer.model"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [],
  "tags": [
    "transformers",
    "tensorboard",
    "safetensors",
    "gemma3",
    "image-text-to-text",
    "medical",
    "french",
    "system-one",
    "decision",
    "calibration",
    "lora",
    "conversational",
    "fr",
    "dataset:bofenghuang/docto-decision-data-fr-v0.1",
    "base_model:google/medgemma-1.5-4b-it",
    "base_model:adapter:google/medgemma-1.5-4b-it",
    "license:other",
    "text-generation-inference",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForMultimodalLM",
    "pipeline_tag": "image-text-to-text",
    "processor": "AutoProcessor"
  },
  "usedStorage": 8759321029
}

Text

This source's terms allow its title, its values and a link here, not its text. It is at https://huggingface.co/bofenghuang/docto-decision-medgemma-1.5-4b-fr-v0.1.