openai

Understanding the Challenges and Updates of OpenAI's GPT-3.5-Turbo-1106 Model

Tal Peretz

Sep 2, 2024 — 2 min read

The OpenAI/ft:gpt-3.5-turbo-1106 model has been a topic of discussion among AI developers and users due to several key issues and updates. This blog post will delve into the primary concerns and provide insights into the current state of the model.

Token Limit Issue

One of the significant issues reported with the gpt-3.5-turbo-1106 is its maximum token limit. Although the official documentation states a limit of 16,385 tokens, users have encountered a restriction at 4,096 tokens. This discrepancy has caused confusion and hindered the model's performance in handling larger inputs. Fortunately, this problem has been addressed in later releases, particularly in version v1.24.0 of the Haystack project.

Performance and User Feedback

Users have reported several performance issues with the gpt-3.5-turbo-1106 model. These include degraded response quality and frequent instances where the model replies with "I'm sorry, I can't do that." Such responses have led many users to revert to the previous gpt-3.5-turbo-0613 model, which has proven to be more reliable.

Fine-Tuning

Fine-tuning capabilities are available for the gpt-3.5-turbo-1106, allowing developers to customize the model for specific use cases. However, there have been issues with accessing fine-tuned models after successful training jobs, resulting in NotFoundError issues for some users. This has created additional challenges in deploying fine-tuned versions of the model effectively.

Deployment and Replacement Plans

Initially, there were plans to point gpt-3.5-turbo to gpt-3.5-turbo-1106 starting December 11, 2023. However, due to the significant issues discovered, these plans have been abandoned. As a result, gpt-3.5-turbo continues to reference the more stable gpt-3.5-turbo-0613 version.

Conclusion

In summary, the gpt-3.5-turbo-1106 model has faced several challenges that have impacted its adoption. While OpenAI has made efforts to address these issues, many users have chosen to stick with the previous version due to its reliability. Developers looking to fine-tune or deploy the gpt-3.5-turbo-1106 should be aware of these challenges and consider the more stable gpt-3.5-turbo-0613 as an alternative.

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