Fix model format with proper config and weights
Browse files- README.md +8 -17
- config.json +0 -0
- model.safetensors +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +56 -0
- vocab.txt +0 -0
README.md
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@@ -6,18 +6,13 @@ library_name: transformers
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pipeline_tag: text-classification
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tags:
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- medical
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source_space: sshan95/medicoder-ai-v2
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---
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#
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This
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## Model Description
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MediCoder AI v2 converted from Space to proper model repository for easier integration and deployment.
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## Usage
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@@ -26,14 +21,10 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("sshan95/medicoder-ai-v2-model")
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model = AutoModelForSequenceClassification.from_pretrained("sshan95/medicoder-ai-v2-model")
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# Your inference code here
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```
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##
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This model was originally deployed as a Space at: https://huggingface.co/spaces/sshan95/medicoder-ai-v2
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## Conversion
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pipeline_tag: text-classification
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tags:
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- medical
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- icd10
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- multilabel-classification
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---
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# MediCoder AI v2 - Fixed Model
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This is a properly formatted version of the MediCoder model for medical code classification.
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## Usage
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tokenizer = AutoTokenizer.from_pretrained("sshan95/medicoder-ai-v2-model")
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model = AutoModelForSequenceClassification.from_pretrained("sshan95/medicoder-ai-v2-model")
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```
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## Configuration
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- **Labels**: 25,719 ICD-10 codes
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- **Architecture**: BERT-based
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- **Task**: Multi-label medical code classification
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config.json
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:592d9849e5d1488ccc511c77c11444975a10fa9572c77749ebf7ff110ec7da6f
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size 517064148
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special_tokens_map.json
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@@ -0,0 +1,7 @@
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"clean_up_tokenization_spaces": false,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"extra_special_tokens": {},
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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vocab.txt
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