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.gitattributes CHANGED
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README.md CHANGED
@@ -1,3 +1,58 @@
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: Qwen/Qwen3-30B-A3B-Instruct-2507
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+ tags:
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+ - medical
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+ - case-studies
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+ - japanese
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+ - qwen
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+ - lora
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+ ---
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+
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+ # rshaikh22/Qwen3_30B_Instruct_CQA_Medical
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+
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+ This is a LoRA (Low-Rank Adaptation) fine-tuned version of Qwen/Qwen3-30B-A3B-Instruct-2507 trained on Japanese medical case studies.
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+
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+ ## Model Details
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+
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+ - **Base Model**: Qwen/Qwen3-30B-A3B-Instruct-2507
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+ - **Training Data**: Japanese medical case studies (~93,563 examples)
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+ - **Fine-tuning Method**: LoRA (Low-Rank Adaptation)
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+ - **Model Type**: LoRA Adapter (requires base model to load)
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+
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+ ## Usage
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+
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+ ### Using with PEFT (Recommended)
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ from peft import PeftModel
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+
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+ # Load base model
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+ base_model = AutoModelForCausalLM.from_pretrained(
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+ "Qwen/Qwen3-30B-A3B-Instruct-2507",
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+ trust_remote_code=True,
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+ torch_dtype="auto"
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-30B-A3B-Instruct-2507", trust_remote_code=True)
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+
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+ # Load LoRA adapter
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+ model = PeftModel.from_pretrained(base_model, "rshaikh22/Qwen3_30B_Instruct_CQA_Medical")
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+ model = model.merge_and_unload() # Optional: merge adapter into base model
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+
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+ # Use the model
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+ prompt = "Your prompt here"
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+ inputs = tokenizer(prompt, return_tensors="pt")
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+ outputs = model.generate(**inputs, max_length=200)
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+ print(tokenizer.decode(outputs[0]))
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+ ```
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+
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+ ### Direct Loading (if adapter is merged)
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model = AutoModelForCausalLM.from_pretrained("rshaikh22/Qwen3_30B_Instruct_CQA_Medical", trust_remote_code=True)
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+ tokenizer = AutoTokenizer.from_pretrained("rshaikh22/Qwen3_30B_Instruct_CQA_Medical", trust_remote_code=True)
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+ ```
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+ }
213
+ },
214
+ "additional_special_tokens": [
215
+ "<|im_start|>",
216
+ "<|im_end|>",
217
+ "<|object_ref_start|>",
218
+ "<|object_ref_end|>",
219
+ "<|box_start|>",
220
+ "<|box_end|>",
221
+ "<|quad_start|>",
222
+ "<|quad_end|>",
223
+ "<|vision_start|>",
224
+ "<|vision_end|>",
225
+ "<|vision_pad|>",
226
+ "<|image_pad|>",
227
+ "<|video_pad|>"
228
+ ],
229
+ "bos_token": null,
230
+ "clean_up_tokenization_spaces": false,
231
+ "eos_token": "<|im_end|>",
232
+ "errors": "replace",
233
+ "extra_special_tokens": {},
234
+ "fast": true,
235
+ "model_max_length": 1010000,
236
+ "pad_token": "<|endoftext|>",
237
+ "split_special_tokens": false,
238
+ "tokenizer_class": "Qwen2Tokenizer",
239
+ "unk_token": null
240
+ }
vocab.json ADDED
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