Update README.md
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README.md
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@@ -49,16 +49,22 @@ Due to the diverse nature of the training data, which includes websites, books,
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import torch
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from transformers import AutoTokenizer, GPT2LMHeadModel
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from transformers import pipeline
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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device_id = 0 if torch.cuda.is_available() else -1
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model = GPT2LMHeadModel.from_pretrained("ytu-ce-cosmos/turkish-gpt2-medium-350m-instruct-v0.1").to(device)
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tokenizer = AutoTokenizer.from_pretrained("ytu-ce-cosmos/turkish-gpt2-medium-350m-instruct-v0.1")
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text_generator = pipeline('text-generation', model=model, tokenizer=tokenizer, device=device_id, max_new_tokens=256)
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def get_model_response(instruction):
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instruction_prompt = f"### Kullanıcı:\n{instruction}\n### Asistan:\n"
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result = text_generator(instruction_prompt)
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generated_response = result[0]['generated_text']
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return generated_response[len(instruction_prompt):]
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model_response = get_model_response("Evde egzersiz yapmanın avantajlarını açıkla.")
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print(model_response)
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"""
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@@ -70,9 +76,11 @@ To use the chat template:
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```python
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chat_generator = pipeline("conversational", model=model, tokenizer=tokenizer, device=device_id, max_new_tokens=256)
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messages = [
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{"role": "user", "content": "Evde egzersiz yapmanın avantajlarını açıkla."}
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]
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chat_outputs = chat_generator(messages)
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print(chat_outputs)
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"""
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import torch
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from transformers import AutoTokenizer, GPT2LMHeadModel
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from transformers import pipeline
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+
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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device_id = 0 if torch.cuda.is_available() else -1
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model = GPT2LMHeadModel.from_pretrained("ytu-ce-cosmos/turkish-gpt2-medium-350m-instruct-v0.1").to(device)
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tokenizer = AutoTokenizer.from_pretrained("ytu-ce-cosmos/turkish-gpt2-medium-350m-instruct-v0.1")
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text_generator = pipeline('text-generation', model=model, tokenizer=tokenizer, device=device_id, max_new_tokens=256)
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def get_model_response(instruction):
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instruction_prompt = f"### Kullanıcı:\n{instruction}\n### Asistan:\n"
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result = text_generator(instruction_prompt)
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generated_response = result[0]['generated_text']
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return generated_response[len(instruction_prompt):]
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model_response = get_model_response("Evde egzersiz yapmanın avantajlarını açıkla.")
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print(model_response)
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"""
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```python
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chat_generator = pipeline("conversational", model=model, tokenizer=tokenizer, device=device_id, max_new_tokens=256)
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messages = [
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{"role": "user", "content": "Evde egzersiz yapmanın avantajlarını açıkla."}
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]
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chat_outputs = chat_generator(messages)
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print(chat_outputs)
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"""
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