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Model: jondurbin/airoboros-7b-gpt4-1.3
Source: Original Platform

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README.md

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+---
+license: cc-by-nc-4.0
+datasets:
+- jondurbin/airoboros-gpt4-1.3
+---
+
+__This version has problems, use if you dare, or wait for 1.4.__
+
+### Overview
+
+This is a qlora fine-tuned 7b parameter LlaMa model, using completely synthetic training data created gpt4 via https://github.com/jondurbin/airoboros
+
+This is mostly an extension of [1.2](https://huggingface.co/jondurbin/airoboros-7b-gpt4-1.2) with a few enhancements:
+
+- All coding instructions have an equivalent " PLAINFORMAT" version now.
+- Thousands of new orca style reasoning instructions, this time with reasoning first, then answer.
+- Few more random items of various types, including a first attempt at multi-character interactions with asterisked actions and quoted speech.
+
+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 previous full fine-tune 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-7b-gpt4-1.3 \
+  --temperature 0.5 \
+  --max-new-tokens 2048 \
+  --no-history
+```
+
+### 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-7b-gpt4-1.3",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 0,
+  "eos_token_id": 1,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 2048,
+  "max_sequence_length": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "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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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.30.0.dev0"
+}

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special_tokens_map.json

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tokenizer_config.json

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