Upload model
Browse files- README.md +2 -2
- config.json +1 -1
- generation_config.json +1 -1
- modelling_cxrrg.py +2 -3
- modelling_uniformer.py +1 -1
README.md
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---
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library_name: transformers
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license: apache-2.0
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datasets:
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- StanfordAIMI/interpret-cxr-test-public
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- StanfordAIMI/interpret-cxr-test-hidden
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---
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# CXRMate-RRG24: Entropy-Augmented Self-Critical Sequence Training for Radiology Report Generation
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---
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datasets:
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- StanfordAIMI/interpret-cxr-test-public
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- StanfordAIMI/interpret-cxr-test-hidden
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library_name: transformers
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license: apache-2.0
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---
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# CXRMate-RRG24: Entropy-Augmented Self-Critical Sequence Training for Radiology Report Generation
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config.json
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"model_type": "vision-encoder-decoder",
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.
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}
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"model_type": "vision-encoder-decoder",
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.40.2"
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}
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generation_config.json
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 4,
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"transformers_version": "4.
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}
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 4,
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"transformers_version": "4.40.2"
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}
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modelling_cxrrg.py
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@@ -7,9 +7,8 @@ from transformers import PreTrainedTokenizerFast, VisionEncoderDecoderModel
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from transformers.configuration_utils import PretrainedConfig
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from transformers.modeling_outputs import Seq2SeqLMOutput
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from transformers.modeling_utils import PreTrainedModel
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from transformers.models.vision_encoder_decoder.configuration_vision_encoder_decoder import
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VisionEncoderDecoderConfig
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)
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from transformers.utils import logging
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from .modelling_uniformer import MultiUniFormerWithProjectionHead
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from transformers.configuration_utils import PretrainedConfig
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from transformers.modeling_outputs import Seq2SeqLMOutput
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from transformers.modeling_utils import PreTrainedModel
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from transformers.models.vision_encoder_decoder.configuration_vision_encoder_decoder import \
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VisionEncoderDecoderConfig
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from transformers.utils import logging
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from .modelling_uniformer import MultiUniFormerWithProjectionHead
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modelling_uniformer.py
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from collections import OrderedDict
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from functools import partial
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from typing import Optional, Tuple, Union
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from math import isqrt
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import torch
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import torch.nn as nn
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from collections import OrderedDict
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from functools import partial
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from math import isqrt
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from typing import Optional, Tuple, Union
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import torch
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import torch.nn as nn
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