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Mistral-7B-v0.2-meditron-turkish is a finetuned Mistral Model version using Freeze technique on Turkish Meditron dataset of malhajar/meditron-7b-tr using SFT Training. This model can answer information about different excplicit ideas in medicine in Turkish and English

Model Description

Prompt Template For Turkish Generation

### KullancΔ±:

Prompt Template For English Generation

### User:

How to Get Started with the Model

Use the code sample provided in the original post to interact with the model.

from transformers import AutoTokenizer,AutoModelForCausalLM
 
model_id = "malhajar/Mistral-7B-v0.2-meditron-turkish"
model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
                                             device_map="auto",
                                             torch_dtype=torch.float16,
                                             revision="main")

tokenizer = AutoTokenizer.from_pretrained(model_id)

question: "Akciğer kanseri nedir?"
# For generating a response
prompt = '''
### KullancΔ±:
{question} 
'''
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
output = model.generate(inputs=input_ids,max_new_tokens=512,pad_token_id=tokenizer.eos_token_id,top_k=50, do_sample=True,
        top_p=0.95)
response = tokenizer.decode(output[0])

print(response)

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 63.34
AI2 Reasoning Challenge (25-Shot) 59.56
HellaSwag (10-Shot) 81.79
MMLU (5-Shot) 60.35
TruthfulQA (0-shot) 66.19
Winogrande (5-shot) 76.24
GSM8k (5-shot) 35.94
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Dataset used to train malhajar/Mistral-7B-v0.2-meditron-turkish

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Evaluation results