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FEAT: Support gemma-3 text part #3077

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merged 5 commits into from
Mar 20, 2025
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Merged

FEAT: Support gemma-3 text part #3077

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243669e
FEAT: Support gemma-3
zky001 Mar 17, 2025
be2fe0b
fix: gguf model_id
Mar 19, 2025
6a33ed6
fix mlx
Mar 19, 2025
cf43f0f
Update xinference/model/llm/llm_family.json
qinxuye Mar 20, 2025
f7559a2
support vllm
qinxuye Mar 20, 2025
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1 change: 1 addition & 0 deletions doc/source/getting_started/installation.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -61,6 +61,7 @@ Currently, supported models include:
- ``QwQ-32B-Preview``, ``QwQ-32B``
- ``marco-o1``
- ``gemma-it``, ``gemma-2-it``
- ``gemma-3-it``, ``gemma-3-27b-it``, ``gemma-3-12b-it``, ``gemma-3-4b-it``, ``gemma-3-1b-it``
- ``orion-chat``, ``orion-chat-rag``
- ``c4ai-command-r-v01``
- ``minicpm3-4b``
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233 changes: 233 additions & 0 deletions xinference/model/llm/llm_family.json
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Expand Up @@ -5786,6 +5786,239 @@
"<start_of_turn>"
]
},
{
"version": 1,
"context_length": 131072,
"model_name": "gemma-3-it",
"model_lang": [
"en"
],
"model_ability": [
"chat"
],
"model_description": "Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.",
"model_specs": [
{
"model_format": "pytorch",
"model_size_in_billions": 1,
"quantizations": [
"none",
"4-bit",
"8-bit"
],
"model_id": "google/gemma-3-1b-it"
},
{
"model_format": "pytorch",
"model_size_in_billions": 4,
"quantizations": [
"none",
"4-bit",
"8-bit"
],
"model_id": "google/gemma-3-4b-it"
},
{
"model_format": "pytorch",
"model_size_in_billions": 12,
"quantizations": [
"none",
"4-bit",
"8-bit"
],
"model_id": "google/gemma-3-12b-it"
},
{
"model_format": "pytorch",
"model_size_in_billions": 27,
"quantizations": [
"none",
"4-bit",
"8-bit"
],
"model_id": "google/gemma-3-27b-it"
},
{
"model_format": "ggufv2",
"model_size_in_billions": 1,
"quantizations": [
"IQ2_M",
"IQ3_M",
"IQ3_XS",
"IQ3_XXS",
"IQ4_NL",
"IQ4_XS",
"Q2_K",
"Q2_K_L",
"Q3_K_L",
"Q3_K_M",
"Q3_K_S",
"Q4_0",
"Q4_1",
"Q4_K_L",
"Q4_K_M",
"Q4_K_S",
"Q5_K_L",
"Q5_K_M",
"Q5_K_S",
"Q6_K",
"Q6_K_L",
"Q8_0",
"bf16"
],
"model_id": "bartowski/google_gemma-3-1b-it-GGUF",
"model_file_name_template": "google_gemma-3-1b-it-{quantization}.gguf"
},
{
"model_format": "ggufv2",
"model_size_in_billions": 4,
"quantizations": [
"IQ2_M",
"IQ3_M",
"IQ3_XS",
"IQ3_XXS",
"IQ4_NL",
"IQ4_XS",
"Q2_K",
"Q2_K_L",
"Q3_K_L",
"Q3_K_M",
"Q3_K_S",
"Q4_0",
"Q4_1",
"Q4_K_L",
"Q4_K_M",
"Q4_K_S",
"Q5_K_L",
"Q5_K_M",
"Q5_K_S",
"Q6_K",
"Q6_K_L",
"Q8_0",
"bf16"
],
"model_id": "bartowski/google_gemma-3-4b-it-GGUF",
"model_file_name_template": "google_gemma-3-4b-it-{quantization}.gguf"
},
{
"model_format": "ggufv2",
"model_size_in_billions": 12,
"quantizations": [
"IQ2_M",
"IQ3_M",
"IQ3_XS",
"IQ3_XXS",
"IQ4_NL",
"IQ4_XS",
"Q2_K",
"Q2_K_L",
"Q3_K_L",
"Q3_K_M",
"Q3_K_S",
"Q4_0",
"Q4_1",
"Q4_K_L",
"Q4_K_M",
"Q4_K_S",
"Q5_K_L",
"Q5_K_M",
"Q5_K_S",
"Q6_K",
"Q6_K_L",
"Q8_0",
"bf16"
],
"model_id": "bartowski/google_gemma-3-12b-it-GGUF",
"model_file_name_template": "google_gemma-3-12b-it-{quantization}.gguf"
},
{
"model_format": "ggufv2",
"model_size_in_billions": 27,
"quantizations": [
"IQ2_M",
"IQ3_M",
"IQ3_XS",
"IQ3_XXS",
"IQ4_NL",
"IQ4_XS",
"Q2_K",
"Q2_K_L",
"Q3_K_L",
"Q3_K_M",
"Q3_K_S",
"Q4_0",
"Q4_1",
"Q4_K_L",
"Q4_K_M",
"Q4_K_S",
"Q5_K_L",
"Q5_K_M",
"Q5_K_S",
"Q6_K",
"Q6_K_L",
"Q8_0",
"bf16"
],
"model_id": "bartowski/google_gemma-3-27b-it-GGUF",
"model_file_name_template": "google_gemma-3-27b-it-{quantization}.gguf"
},
{
"model_format": "mlx",
"model_size_in_billions": 1,
"quantizations": [
"4bit",
"6bit",
"8bit",
"fp16"
],
"model_id": "mlx-community/gemma-3-1b-it-{quantization}"
},
{
"model_format": "mlx",
"model_size_in_billions": 4,
"quantizations": [
"4bit",
"6bit",
"8bit",
"fp16"
],
"model_id": "mlx-community/gemma-3-4b-it-{quantization}"
},
{
"model_format": "mlx",
"model_size_in_billions": 12,
"quantizations": [
"4bit",
"6bit",
"8bit",
"fp16"
],
"model_id": "mlx-community/gemma-3-12b-it-{quantization}"
},
{
"model_format": "mlx",
"model_size_in_billions": 27,
"quantizations": [
"4bit",
"6bit",
"8bit",
"fp16"
],
"model_id": "mlx-community/gemma-3-27b-it-{quantization}"
}
],
"chat_template": "{{ 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",
"stop_token_ids": [
1,
105,
106
],
"stop": [
"<eos>",
"<end_of_turn>",
"<start_of_turn>"
]
},
{
"version": 1,
"context_length": 8192,
Expand Down
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