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  - tr
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  pipeline_tag: text-generation
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  ---
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-
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- # Model Card for Model ID
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-
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- <!-- Provide a quick summary of what the model is/does. -->
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-
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-
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-
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- ## Model Details
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-
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  ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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-
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  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [Umar Igan]
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- - **Model type:** [LLama-2-7B-chat]
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- - **Language(s) (NLP):** [Turkish]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [Trendyol-LLM-7b-chat-v0.1]
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-
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- ### Recommendations
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-
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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  ## How to Get Started with the Model
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- Use the code below to get started with the model.
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-
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- [More Information Needed]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Training Details
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  - tr
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  pipeline_tag: text-generation
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  ---
 
 
 
 
 
 
 
 
 
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  ### Model Description
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  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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+ - **Developed by:** Umar Igan
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+ - **Model type:** LLama-2-7B-chat
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+ - **Language(s) (NLP):** Turkish
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+ - **Finetuned from model:** Trendyol-LLM-7b-chat-v0.1
 
 
 
 
 
 
 
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  ## How to Get Started with the Model
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+ ```
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+ # Use a pipeline as a high-level helper
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+ from transformers import pipeline
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+
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+ pipe = pipeline("text-generation", model="umarigan/Trendyol-LLM-7b-chat-v0.1-DPO")
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+
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+ # Generate text
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+ sequences = pipe(
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+ "büyük dil modellerinin finans alanındaki kullanımları nelerdir",
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+ do_sample=True,
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+ temperature=0.7,
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+ top_p=0.9,
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+ num_return_sequences=1,
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+ max_length=200,
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+ )
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+ print(sequences[0]['generated_text'])
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+
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+ Question: büyük dil modellerinin finans alanındaki kullanımları nelerdir?
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+ Answer: Çok büyük dil modelleri, özellikle de Transformer gibi, karmaşık dil görevlerinin üstesinden gelmek için tasarlanmışlardır. Bu, finansal piyasalardaki veri işleme, fiyat tahmini ve analizleri, finansal haberler ve raporlama gibi süreçleri içerir. Ayrıca, büyük dil modelleri, doğal dil işleme, metin sınıflandırma ve soru cevaplama gibi görevlerin yanı sıra, müşteri hizmetleri gibi insan etkileşimi gerektiren finansal hizmetlerde de kullanılmaktadır.
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+ ```
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  ## Training Details
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