shawhin/Qwen2.5-0.5B-DPO

README.md

@@ -7,20 +7,10 @@ tags:
 - trl
 - dpo
 licence: license
-license: apache-2.0
-datasets:
-- shawhin/youtube-titles-dpo
 ---
 
 # Model Card for Qwen2.5-0.5B-DPO
 
-Model fine-tuned on YouTube title preferences for my [YouTube channel](https://www.youtube.com/@ShawhinTalebi).
-
-[Preference dataset](https://huggingface.co/datasets/shawhin/youtube-titles-dpo) <br>
-YouTube video: coming soon! <br>
-Blog post: coming soon!
-
-
 This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct).
 It has been trained using [TRL](https://github.com/huggingface/trl).
 
@@ -29,11 +19,9 @@ It has been trained using [TRL](https://github.com/huggingface/trl).
 ```python
 from transformers import pipeline
 
-video_idea = "intro independent component analysis"
-prompt = f"Given the YouTube video idea write an engaging title.\n\n**Video Idea**: {video_idea}\n\n**Additional Guidance**:\n- Title should be between 30 and 75 characters long\n- Only return the title idea, nothing else!"
-
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
 generator = pipeline("text-generation", model="shawhin/Qwen2.5-0.5B-DPO", device="cuda")
-output = generator([{"role": "user", "content": prompt}], max_new_tokens=128, return_full_text=False)[0]
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
 print(output["generated_text"])
 ```
 

model.safetensors

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training_args.bin

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