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Model: jondurbin/airoboros-13b-gpt4-1.2
Source: Original Platform

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README.md

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+---
+license: cc-by-nc-4.0
+datasets:
+- jondurbin/airoboros-gpt4-1.2
+---
+
+### Overview
+
+This is a qlora fine-tuned 13b parameter LlaMa model, using completely synthetic training data created gpt4 via https://github.com/jondurbin/airoboros
+
+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.
+
+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:
+- coding
+- math/reasoning (using orca style ELI5 instruction/response pairs)
+- trivia
+- role playing
+- multiple choice and fill-in-the-blank
+- context-obedient question answering
+- theory of mind
+- misc/general
+
+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:
+
+```
+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: 
+```
+
+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).
+
+### Usage
+
+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.
+```
+pip install git+https://github.com/jondurbin/FastChat
+```
+
+Be sure you are pulling the latest branch!
+
+Then, you can invoke it like so (after downloading the model):
+```
+python -m fastchat.serve.cli \
+  --model-path airoboros-13b-gpt4-1.2 \
+  --temperature 0.5 \
+  --max-new-tokens 2048 \
+  --no-history
+```
+
+Alternatively, please check out TheBloke's quantized versions:
+
+- https://huggingface.co/TheBloke/airoboros-13B-gpt4-1.2-GPTQ
+- https://huggingface.co/TheBloke/airoboros-13B-gpt4-1.2-GGML
+
+### Coding updates from gpt4/1.1:
+
+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.
+
+It's not guaranteed to work all the time, but mostly it does seem to work as expected.
+
+So for example, instead of:
+```
+Implement the Snake game in python.
+```
+
+You would use:
+```
+Implement the Snake game in python.  PLAINFORMAT
+```
+
+### Other updates from gpt4/1.1:
+
+- Several hundred role-playing data.
+- 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).
+- Many more coding examples in various languages, including some that use specific libraries (pandas, numpy, tensorflow, etc.)
+
+### Usage and License Notices
+
+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:
+
+- the base model is LLaMa, which has it's own special research license
+- 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
+
+So, to reiterate: this model (and datasets) cannot be used commercially.

config.json

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+{
+  "_name_or_path": "airoboros-13b-gpt4-1.2",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 0,
+  "eos_token_id": 1,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 2048,
+  "max_sequence_length": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 40,
+  "pad_token_id": -1,
+  "rms_norm_eps": 1e-06,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.30.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

configuration.json

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generation_config.json

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+  "eos_token_id": 1,
+  "pad_token_id": -1,
+  "transformers_version": "4.30.0.dev0"
+}

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