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README.md
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@@ -15,6 +15,7 @@ At the very core of the development of this model is the desire to make sure tha
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Test this out and see if you find anything interesting or intriguing. I will keep iterating more versions but this one seems like a fun and useful way to start.
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# Phased Training Methodology
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Leveraging this dataset, we've adopted a phased training methodology that focuses sequentially on different dataset components, namely "System" and "Instruction," across separate training phases. This approach allows models to build layered understandings from general systemic insights to specific instructional cues, enriching their generative output with both broad contextual awareness and detailed, topic-specific knowledge.
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**If you'd like to train your own version, here is the full notebook to recreate the training on Unsloth yourself (https://colab.research.google.com/drive/1828t77iO2nLRXVfB8HoI11eFu-79-Oe7?usp=sharing). You'll just have to drop in the train.jsonl from the Dataset repo (https://huggingface.co/datasets/Severian/Internal-Knowledge-Map) into your Colab directory and rename it dataset.jsonl**
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3. **Assess the Innovation Level**: Responses that suggest new or unconventional uses demonstrate the model's ability to synthesize information creatively and offer innovative solutions.
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4. **Evaluate Environmental Consciousness**: Nexus-7B's approach reflects a subtle yet significant emphasis on sustainability, indicating an advanced integration of ecological awareness into problem-solving strategies.
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## **Most people recognize bees for their role in pollination, but their contributions to ecosystems extend far beyond that. Can you elaborate on the less commonly known yet crucial roles that bees play in supporting biodiversity and ecosystem health?**
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### Base:
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4. **Uncommon Insights**: Pay attention to unique or less commonly discussed roles that bees play, as highlighted by Nexus-7B. These insights can reveal the model's ability to go beyond surface-level knowledge and explore complex ecological dynamics.
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## Training Snapshot
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```
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Test this out and see if you find anything interesting or intriguing. I will keep iterating more versions but this one seems like a fun and useful way to start.
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---
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# Phased Training Methodology
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Leveraging this dataset, we've adopted a phased training methodology that focuses sequentially on different dataset components, namely "System" and "Instruction," across separate training phases. This approach allows models to build layered understandings from general systemic insights to specific instructional cues, enriching their generative output with both broad contextual awareness and detailed, topic-specific knowledge.
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**If you'd like to train your own version, here is the full notebook to recreate the training on Unsloth yourself (https://colab.research.google.com/drive/1828t77iO2nLRXVfB8HoI11eFu-79-Oe7?usp=sharing). You'll just have to drop in the train.jsonl from the Dataset repo (https://huggingface.co/datasets/Severian/Internal-Knowledge-Map) into your Colab directory and rename it dataset.jsonl**
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3. **Assess the Innovation Level**: Responses that suggest new or unconventional uses demonstrate the model's ability to synthesize information creatively and offer innovative solutions.
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4. **Evaluate Environmental Consciousness**: Nexus-7B's approach reflects a subtle yet significant emphasis on sustainability, indicating an advanced integration of ecological awareness into problem-solving strategies.
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## **Most people recognize bees for their role in pollination, but their contributions to ecosystems extend far beyond that. Can you elaborate on the less commonly known yet crucial roles that bees play in supporting biodiversity and ecosystem health?**
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### Base:
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4. **Uncommon Insights**: Pay attention to unique or less commonly discussed roles that bees play, as highlighted by Nexus-7B. These insights can reveal the model's ability to go beyond surface-level knowledge and explore complex ecological dynamics.
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## Training Snapshot
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```
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