初始化项目，由ModelHub XC社区提供模型
Model: malhajar/Mistral-7B-v0.2-meditron-turkish Source: Original Platform
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README.md
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README.md
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---
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language:
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- tr
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- en
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license: apache-2.0
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datasets:
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- malhajar/meditron-tr
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model-index:
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- name: Mistral-7B-v0.2-meditron-turkish
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 59.56
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 81.79
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 60.35
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 66.19
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 76.24
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 35.94
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
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name: Open LLM Leaderboard
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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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`](https://huggingface.co/datasets/malhajar/meditron-tr) using SFT Training.
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This model can answer information about different excplicit ideas in medicine in Turkish and English
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### Model Description
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- **Finetuned by:** [`Mohamad Alhajar`](https://www.linkedin.com/in/muhammet-alhajar/)
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- **Language(s) (NLP):** Turkish,English
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- **Finetuned from model:** [`mistralai/Mistral-7B-Instruct-v0.2`](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
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### Prompt Template For Turkish Generation
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```
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### Kullancı:
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```
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### Prompt Template For English Generation
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```
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### User:
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```
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## How to Get Started with the Model
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Use the code sample provided in the original post to interact with the model.
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```python
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from transformers import AutoTokenizer,AutoModelForCausalLM
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model_id = "malhajar/Mistral-7B-v0.2-meditron-turkish"
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model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
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device_map="auto",
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torch_dtype=torch.float16,
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revision="main")
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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question: "Akciğer kanseri nedir?"
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# For generating a response
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prompt = '''
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### Kullancı:
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{question}
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'''
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids
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output = model.generate(inputs=input_ids,max_new_tokens=512,pad_token_id=tokenizer.eos_token_id,top_k=50, do_sample=True,
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top_p=0.95)
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response = tokenizer.decode(output[0])
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print(response)
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_malhajar__Mistral-7B-v0.2-meditron-turkish)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |63.34|
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|AI2 Reasoning Challenge (25-Shot)|59.56|
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|HellaSwag (10-Shot) |81.79|
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|MMLU (5-Shot) |60.35|
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|TruthfulQA (0-shot) |66.19|
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|Winogrande (5-shot) |76.24|
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|GSM8k (5-shot) |35.94|
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