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README.md
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---
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### Description:
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This is a llama 13b model merge of the LoRA with the same name.
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### Objective for this project:
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To create a model that upholds a logical thread, regardless of whether the output is verbose or concise. Training has been performed on a version of the pile of sets, reduced to 40% of its original size, to expedite training iterations. I personally utilize this model as an aid for storytelling and writing. While it serves this purpose adequately, I still perceive this version as a prototype.
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### Prompt format:
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Stanford Alpaca
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The prompt should start on a new line after "### Response:"
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- For examples with a non-empty input field:
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```
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Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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### Instruction:
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{instruction}
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### Input:
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{input}
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### Response:
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```
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- For examples with an empty input field:
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```
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Below is an instruction that describes a task. Write a response that appropriately completes the request.
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### Instruction:
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{instruction}
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### Response:
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```
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### Training information
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- 2 Epochs
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- 64 / 32 R / A
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- 1024 Cutoff
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- 19 hours on an A6000
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### Data used in training
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All cleaned and scrubbed in various ways then culled to various degrees.
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- Camel biology, physics, chemistry, math, and AI society
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- Alpaca evol instruct
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- GPTeacher Instruct
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- Alpaca GPT4
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- Dolly Databricks
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### Plans for the future, a brief overview:
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- Pivot to a conversational format going forward
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- Train another 13b LoRA against the entirety of my pile of sets rather than just a portion of it for Mk2
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- Train 30b on the Mk2 pile of sets
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- Expand the story generation capabilities and likely more for Mk3
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### Model used for training and other information:
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https://huggingface.co/PocketDoc/llama-13b-gptq-4bit-128g
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Merge model:
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https://huggingface.co/huggyllama/llama-13b
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### Disclaimer:
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It has not been aligned and no warranty is given for the quality or safety of its outputs.
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