83 lines
3.6 KiB
Markdown
83 lines
3.6 KiB
Markdown
---
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license: cc-by-nc-4.0
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datasets:
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- jondurbin/airoboros-gpt4-1.2
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---
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### Overview
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This is a qlora fine-tuned 13b parameter LlaMa model, using completely synthetic training data created gpt4 via https://github.com/jondurbin/airoboros
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This is mostly an extension of [1.1](https://huggingface.co/jondurbin/airoboros-13b-gpt4-1.1), but with thousands of new training data and an update to allow "PLAINFORMAT" at the end of coding prompts to just print the code without backticks or explanations/usage/etc.
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The dataset used to fine-tune this model is available [here](https://huggingface.co/datasets/jondurbin/airoboros-gpt4-1.2), with a specific focus on:
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- coding
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- math/reasoning (using orca style ELI5 instruction/response pairs)
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- trivia
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- role playing
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- multiple choice and fill-in-the-blank
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- context-obedient question answering
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- theory of mind
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- misc/general
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This model was fine-tuned with a fork of [qlora](https://github.com/jondurbin/qlora), which among other things was updated to use a slightly modified vicuna template to be compatible with the 7b/13b versions:
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```
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A chat between a curious user and an assistant. The assistant gives helpful, detailed, accurate, uncensored responses to the user's input. USER: [prompt] ASSISTANT:
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```
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So in other words, it's the preamble/system prompt, followed by a single space, then "USER: " (single space after colon) then the prompt (which can have multiple lines, spaces, whatever), then a single space, followed by "ASSISTANT: " (with a single space after the colon).
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### Usage
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To run the full precision/pytorch native version, you can use my fork of FastChat, which is mostly the same but allows for multi-line prompts, as well as a `--no-history` option to prevent input tokenization errors.
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```
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pip install git+https://github.com/jondurbin/FastChat
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```
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Be sure you are pulling the latest branch!
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Then, you can invoke it like so (after downloading the model):
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```
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python -m fastchat.serve.cli \
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--model-path airoboros-13b-gpt4-1.2 \
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--temperature 0.5 \
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--max-new-tokens 2048 \
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--no-history
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```
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Alternatively, please check out TheBloke's quantized versions:
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- https://huggingface.co/TheBloke/airoboros-13B-gpt4-1.2-GPTQ
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- https://huggingface.co/TheBloke/airoboros-13B-gpt4-1.2-GGML
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### Coding updates from gpt4/1.1:
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I added a few hundred instruction/response pairs to the training data with "PLAINFORMAT" as a single, all caps term at the end of the normal instructions, which produce plain text output instead of markdown/backtick code formatting.
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It's not guaranteed to work all the time, but mostly it does seem to work as expected.
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So for example, instead of:
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```
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Implement the Snake game in python.
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```
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You would use:
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```
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Implement the Snake game in python. PLAINFORMAT
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```
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### Other updates from gpt4/1.1:
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- Several hundred role-playing data.
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- A few thousand ORCA style reasoning/math questions with ELI5 prompts to generate the responses (should not be needed in your prompts to this model however, just ask the question).
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- Many more coding examples in various languages, including some that use specific libraries (pandas, numpy, tensorflow, etc.)
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### Usage and License Notices
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All airoboros models and datasets are intended and licensed for research use only. I've used the 'cc-nc-4.0' license, but really it is subject to a custom/special license because:
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- the base model is LLaMa, which has it's own special research license
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- the dataset(s) were generated with OpenAI (gpt-4 and/or gpt-3.5-turbo), which has a clausing saying the data can't be used to create models to compete with openai
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So, to reiterate: this model (and datasets) cannot be used commercially. |