Update README.md

README.md

@@ -17,192 +17,84 @@ tags:
 
 ## Model Details
 
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
+This model is a fine-tuned version of Qwen2.5-1.5B-Instruct for medical reasoning in Turkish. The model was trained on ituperceptron/turkish_medical_reasoning dataset, which contains 
+instruction-tuned examples focused on clinical reasoning, diagnosis, patient care, and medical decision-making.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
+### Model Description
 
-<!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Developed by:** Rustam Shiriyev
+- **Language(s) (NLP):** Turkish
+- **License:** MIT
+- **Finetuned from model:** unsloth/Qwen2.5-1.5B-Instruct
+ 
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
+ - Medical Q&A in Turkish
+ - Clinical reasoning tasks (educational or non-diagnostic)
+ - Research on medical domain adaptation and multilingual LLMs
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
+This model is intended for research and educational purposes only. It should not be used for real-world medical decision-making or patient care.
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
 
 ## How to Get Started with the Model
 
 Use the code below to get started with the model.
 
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
+```python
 
+from huggingface_hub import login
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
 
+login(token="")
 
-## Model Examination [optional]
+tokenizer = AutoTokenizer.from_pretrained("unsloth/Qwen2.5-1.5B-Instruct",)
+base_model = AutoModelForCausalLM.from_pretrained(
+    "unsloth/Qwen2.5-1.5B-Instruct",
+    device_map={"": 0}, token=""
+)
 
-<!-- Relevant interpretability work for the model goes here -->
+model = PeftModel.from_pretrained(base_model,"Rustamshry/Qwen2.5-1.5B-turkish-medical-R1")
 
-[More Information Needed]
 
-## Environmental Impact
+question = "Medüller tiroid karsinomu örneklerinin elektron mikroskopisinde gözlemlenen spesifik özellik nedir?"
 
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+prompt = (
 
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+    "### Talimat:\n"
+    "Siz bir tıbb alanında uzmanlaşmış yapay zeka asistanısınız. Gelen soruları yalnızca Türkçe olarak, "
+    "açıklayıcı bir şekilde yanıtlayın.\n\n"
+     f"### Soru:\n{question.strip()}\n\n"
+     f"### Cevap:\n"
 
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+)
 
-## Technical Specifications [optional]
+input_ids = tokenizer(prompt, return_tensors="pt").to(model.device)
 
-### Model Architecture and Objective
+outputs = model.generate(
+    **input_ids,
+    max_new_tokens=2048,
+)
 
-[More Information Needed]
+print(tokenizer.decode(outputs[0]))
+```
 
-### Compute Infrastructure
+## Training Data
 
-[More Information Needed]
+- Dataset: ituperceptron/turkish_medical_reasoning; Translated version of FreedomIntelligence/medical-o1-reasoning-SFT (Turkish, ~7K examples)
 
-#### Hardware
 
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
+## Evaluation
 
-[More Information Needed]
+No formal quantitative evaluation yet.
 
-## Model Card Contact
 
-[More Information Needed]
 ### Framework versions
 
 - PEFT 0.15.2