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Browse files- README.md +1 -1
- modeling_internvl_chat.py +3 -1
README.md
CHANGED
@@ -2,7 +2,7 @@
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license: mit
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pipeline_tag: image-text-to-text
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library_name: transformers
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base_model:
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- OpenGVLab/InternViT-300M-448px
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- internlm/internlm2_5-7b-chat
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base_model_relation: merge
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license: mit
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pipeline_tag: image-text-to-text
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library_name: transformers
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base_model:
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- OpenGVLab/InternViT-300M-448px
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- internlm/internlm2_5-7b-chat
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base_model_relation: merge
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modeling_internvl_chat.py
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@@ -38,7 +38,7 @@ class InternVLChatModel(PreTrainedModel):
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_supports_flash_attn_2 = True
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_no_split_modules = ['InternVisionModel', 'LlamaDecoderLayer', 'InternLM2DecoderLayer']
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def __init__(self, config: InternVLChatConfig, vision_model=None, language_model=None):
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super().__init__(config)
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assert version_cmp(transformers.__version__, '4.36.2', 'ge')
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@@ -50,6 +50,8 @@ class InternVLChatModel(PreTrainedModel):
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self.num_image_token = int((image_size // patch_size) ** 2 * (config.downsample_ratio ** 2))
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self.downsample_ratio = config.downsample_ratio
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self.ps_version = config.ps_version
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logger.info(f'num_image_token: {self.num_image_token}')
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logger.info(f'ps_version: {self.ps_version}')
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_supports_flash_attn_2 = True
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_no_split_modules = ['InternVisionModel', 'LlamaDecoderLayer', 'InternLM2DecoderLayer']
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def __init__(self, config: InternVLChatConfig, vision_model=None, language_model=None, use_flash_attn=True):
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super().__init__(config)
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assert version_cmp(transformers.__version__, '4.36.2', 'ge')
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self.num_image_token = int((image_size // patch_size) ** 2 * (config.downsample_ratio ** 2))
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self.downsample_ratio = config.downsample_ratio
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self.ps_version = config.ps_version
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config.vision_config.use_flash_attn = True if use_flash_attn else False
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config.llm_config.attn_implementation = 'flash_attention_2' if use_flash_attn else 'eager'
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logger.info(f'num_image_token: {self.num_image_token}')
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logger.info(f'ps_version: {self.ps_version}')
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