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<img src="https://huggingface.co/Vezora/Agent-7b-v1/resolve/main/Designer.png" width="400" height="500" />
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# Model Overview
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The base model used for training is `CallComply/openchat-3.5-0106-128k`, which features a context length of 128k. This model was trained on 31,000 examples from the `m-a-p/Code-Feedback` dataset. This dataset aids the model in interactive code performance, enabling it to self-improve with interpreter and human feedback. It is ideal for applications like TaskWeaver, which helps automatically build code, or OpenInterpreter, which assists you in writing code or serves as a general agent.
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<img src="https://huggingface.co/Vezora/Agent-7b-v1/resolve/main/Designer.png" width="400" height="500" />
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[My Kofi](https://ko-fi.com/nicolasmejiapetit)
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# Model Overview
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The base model used for training is `CallComply/openchat-3.5-0106-128k`, which features a context length of 128k. This model was trained on 31,000 examples from the `m-a-p/Code-Feedback` dataset. This dataset aids the model in interactive code performance, enabling it to self-improve with interpreter and human feedback. It is ideal for applications like TaskWeaver, which helps automatically build code, or OpenInterpreter, which assists you in writing code or serves as a general agent.
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