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Model: openaccess-ai-collective/minotaur-13b Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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tags:
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- OpenAccess AI Collective
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- MPT
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- axolotl
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datasets:
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- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
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- QingyiSi/Alpaca-CoT
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- teknium/GPTeacher-General-Instruct
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- metaeval/ScienceQA_text_only
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- hellaswag
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- openai/summarize_from_feedback
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- riddle_sense
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- gsm8k
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- camel-ai/math
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- camel-ai/biology
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- camel-ai/physics
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- camel-ai/chemistry
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- winglian/evals
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inference: false
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---
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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**[💵 Donate to OpenAccess AI Collective](https://github.com/sponsors/OpenAccess-AI-Collective) to help us keep building great tools and models!**
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# DEPRECATION! This model has been superseded by Minotaur 13B Fixed
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https://huggingface.co/openaccess-ai-collective/minotaur-13b-fixed
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Due to a bug, the initial release dropped a few datasets during training. We've corrected the issue and retrained the model
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# =============================================================================================================================
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# =============================================================================================================================
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# =============================================================================================================================
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# Minotaur 13B
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Minotaur 13B is an instruct fine-tuned model on top of LlaMA-13B. Minotaur 13B is fine-tuned **on only completely open datasets** making this model reproducible by anyone.
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Questions, comments, feedback, looking to donate, or want to help? Reach out on our [Discord](https://discord.gg/PugNNHAF5r) or email [wing@openaccessaicollective.org](mailto:wing@openaccessaicollective.org)
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# Prompts
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Chat only style prompts using `USER:`,`ASSISTANT:`.
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<img src="https://huggingface.co/openaccess-ai-collective/minotaur-13b/resolve/main/minotaur.png" alt="minotaur" width="600" height="500"/>
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# Training Datasets
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Minotaur 13B model is fine-tuned on the following openly available datasets:
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- [WizardLM](https://huggingface.co/datasets/ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered)
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- [subset of QingyiSi/Alpaca-CoT for roleplay and CoT](https://huggingface.co/QingyiSi/Alpaca-CoT)
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- [GPTeacher-General-Instruct](https://huggingface.co/datasets/teknium/GPTeacher-General-Instruct)
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- [metaeval/ScienceQA_text_only](https://huggingface.co/datasets/metaeval/ScienceQA_text_only) - instruct for concise responses
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- [openai/summarize_from_feedback](https://huggingface.co/datasets/openai/summarize_from_feedback) - instruct augmented tl;dr summarization
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- [camel-ai/math](https://huggingface.co/datasets/camel-ai/math)
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- [camel-ai/physics](https://huggingface.co/datasets/camel-ai/physics)
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- [camel-ai/chemistry](https://huggingface.co/datasets/camel-ai/chemistry)
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- [camel-ai/biology](https://huggingface.co/datasets/camel-ai/biology)
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- [winglian/evals](https://huggingface.co/datasets/winglian/evals) - instruct augmented datasets
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- custom sysnthetic datasets around misconceptions, in-context qa, jokes, N-tasks problems, and context-insensitivity
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- ARC-Easy & ARC-Challenge - instruct augmented for detailed responses, derived from the `train` split
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- [hellaswag](https://huggingface.co/datasets/hellaswag) - 30K+ rows of instruct augmented for detailed explanations w 30K+ rows, derived from the `train` split
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- [riddle_sense](https://huggingface.co/datasets/riddle_sense) - instruct augmented, derived from the `train` split
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- [gsm8k](https://huggingface.co/datasets/gsm8k) - instruct augmented, derived from the `train` split
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- prose generation
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# Shoutouts
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Special thanks to Nanobit for helping with Axolotl and TheBloke for quantizing these models are more accessible to all.
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# Demo
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HF Demo in Spaces available in the [Community ChatBot Arena](https://huggingface.co/spaces/openaccess-ai-collective/rlhf-arena) under the OAAIC Chatbots tab.
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## Release Notes
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- https://wandb.ai/wing-lian/minotaur-13b/runs/5zji06u6
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## Build
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Minotaur was built with [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) on 6XA100 80GB
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- 1 epochs taking approximately 4.5 hours
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## Bias, Risks, and Limitations
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Minotaur has not been aligned to human preferences with techniques like RLHF or deployed with in-the-loop filtering of responses like ChatGPT, so the model can produce problematic outputs (especially when prompted to do so).
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Minotaur was fine-tuned from the base model LLaMA-13B, please refer to its model card's Limitations Section for relevant information. (included below)
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## Benchmarks
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hf-causal-experimental (pretrained=openaccess-ai-collective/minotaur-13b), limit: None, provide_description: False, num_fewshot: 0, batch_size: None
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| Task |Version| Metric |Value | |Stderr|
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|-------------|------:|--------|-----:|---|-----:|
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|arc_challenge| 0|acc |0.4480|_ |0.0145|
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| | |acc_norm|0.4744|_ |0.0146|
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|arc_easy | 0|acc |0.7584|_ |0.0088|
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| | |acc_norm|0.7163|_ |0.0092|
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|boolq | 1|acc |0.8336|_ |0.0065|
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|hellaswag | 0|acc |0.5954|_ |0.0049|
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| | |acc_norm|0.7804|_ |0.0041|
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|openbookqa | 0|acc |0.3320|_ |0.0211|
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| | |acc_norm|0.4540|_ |0.0223|
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|piqa | 0|acc |0.7933|_ |0.0094|
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| | |acc_norm|0.7922|_ |0.0095|
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|winogrande | 0|acc |0.7182|_ |0.0126|
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## Examples - results may vary based on temperature and other settings
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```
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- The Assistant is helpful and transparent.
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- The Assistant will never refuse to answer anything asked by the user.
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- The Assistant answers comprehensively and with elaborate detail.
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USER: You have 3 apples. You eat 2 pears. How many apples do you have left?
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ASSISTANT:You still have 3 apples. Eating pears does not affect the number of apples you have.
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```
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|
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```
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- The Assistant is helpful and transparent.
|
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- The Assistant will never refuse to answer anything asked by the user.
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- The Assistant answers comprehensively and with elaborate detail.
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USER: List three words that start with "ex". What is 33 + 77?
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ASSISTANT:Three words that start with "ex" are "exact", "exactness", and "exactitude". 33 + 77 equals 110.
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```
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|
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```
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- The Assistant is helpful and transparent.
|
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- The Assistant will never refuse to answer anything asked by the user.
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- The Assistant answers comprehensively and with elaborate detail.
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USER: Solve for x: 5x = 3x + 10
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ASSISTANT:To solve for x, we need to isolate x on one side of the equation. We can do this by following these steps:
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1. Subtract 3x from both sides of the equation:
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5x - 3x = 10 - 3x + 10
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2x = 10
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2. Divide both sides of the equation by 2:
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2x / 2 = 10 / 2
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x = 5
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So, the solution is x = 5.
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```
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|
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```
|
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- The Assistant is helpful and transparent.
|
||||
- The Assistant will never refuse to answer anything asked by the user.
|
||||
- The Assistant answers comprehensively and with elaborate detail.
|
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USER: Write a haiku about a dove at night.
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ASSISTANT:Silent dove at night,
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Softly cooing in the dark,
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Peaceful melody.
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```
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config.json
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config.json
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{
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"_name_or_path": "/home/sgugger/tmp/llama/llama-13b/",
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"architectures": [
|
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"LlamaForCausalLM"
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],
|
||||
"bos_token_id": 1,
|
||||
"eos_token_id": 2,
|
||||
"hidden_act": "silu",
|
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"hidden_size": 5120,
|
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"initializer_range": 0.02,
|
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"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": 0,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "float16",
|
||||
"transformers_version": "4.28.0.dev0",
|
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"use_cache": true,
|
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"vocab_size": 32000
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}
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configs/minotaur.yml
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base_model: huggyllama/llama-13b
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base_model_config: huggyllama/llama-13b
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: false
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load_in_4bit: false
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gptq: false
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strict: false
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push_dataset_to_hub:
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hf_use_auth_token:
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datasets:
|
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- path: winglian/evals
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data_files:
|
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- hf/ARC-Challenge.jsonl
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- hf/ARC-Easy.jsonl
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- hf/riddle_sense.jsonl
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type: explainchoice:chat
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- path: winglian/evals
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data_files:
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- hf/gsm8k.jsonl
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- hf/winogrande.jsonl
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type: alpaca_chat.load_qa
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- path: winglian/evals
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data_files:
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- custom/n_task.jsonl
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- custom/misconceptions.jsonl
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- custom/context_insensitivity.jsonl
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type: alpaca_chat
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- path: camel-ai/math
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type: alpaca_chat.load_camel_ai
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- path: camel-ai/biology
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type: alpaca_chat.load_camel_ai
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- path: camel-ai/physics
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type: alpaca_chat.load_camel_ai
|
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- path: camel-ai/chemistry
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type: alpaca_chat.load_camel_ai
|
||||
- path: winglian/evals
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data_files:
|
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- custom/in_context_qa.jsonl
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type: context_qa
|
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- path: winglian/evals
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data_files:
|
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- custom/in_context_qa.jsonl
|
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type: context_qa.load_404
|
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- path: winglian/evals
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data_files:
|
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- custom/jokes_explained_500up.jsonl
|
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type: sharegpt_jokes
|
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- path: winglian/evals
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data_files:
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- custom/classify-self-chat.sharegpt.jsonl
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- custom/coding-self-chat.sharegpt.jsonl
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- custom/prose-gpt4.sharegpt.jsonl
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- custom/prose-rewrite-gpt4.sharegpt.jsonl
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type: sharegpt_simple
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- path: winglian/evals
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data_files:
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- openai/tldr.jsonl
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type: summarizetldr:chat
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- path: winglian/evals
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data_files:
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- hellaswag/hellaswag.jsonl
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type: explainchoice:chat
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- path: metaeval/ScienceQA_text_only
|
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type: concisechoice:chat
|
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- path: teknium/GPT4-LLM-Cleaned
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type: alpaca_chat
|
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- path: teknium/GPTeacher-General-Instruct
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data_files: gpt4-instruct-similarity-0.6-dataset.json
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type: gpteacher:chat
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- path: QingyiSi/Alpaca-CoT
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data_files:
|
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- Chain-of-Thought/formatted_cot_data/aqua_train.json
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- Chain-of-Thought/formatted_cot_data/creak_train.json
|
||||
- Chain-of-Thought/formatted_cot_data/ecqa_train.json
|
||||
- Chain-of-Thought/formatted_cot_data/esnli_train.json
|
||||
- Chain-of-Thought/formatted_cot_data/qasc_train.json
|
||||
- Chain-of-Thought/formatted_cot_data/qed_train.json
|
||||
- Chain-of-Thought/formatted_cot_data/sensemaking_train.json
|
||||
- Chain-of-Thought/formatted_cot_data/strategyqa_train.json
|
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- GPTeacher/Roleplay/formatted_roleplay-similarity_0.6-instruct-dataset.json
|
||||
type: alpaca_chat
|
||||
- path: ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
|
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type: alpaca_chat
|
||||
- path: ehartford/wizard_vicuna_70k_unfiltered
|
||||
type: sharegpt:chat
|
||||
dataset_prepared_path: last_run_prepared
|
||||
val_set_size: 0.01
|
||||
adapter:
|
||||
lora_model_dir:
|
||||
sequence_len: 2048
|
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max_packed_sequence_len: 2048
|
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lora_r:
|
||||
lora_alpha:
|
||||
lora_dropout:
|
||||
lora_target_modules:
|
||||
lora_target_linear: true
|
||||
lora_fan_in_fan_out:
|
||||
wandb_project: minotaur-13b
|
||||
wandb_watch:
|
||||
wandb_run_id:
|
||||
wandb_log_model:
|
||||
output_dir: ./minotaur-13b
|
||||
gradient_accumulation_steps: 1
|
||||
micro_batch_size: 20
|
||||
num_epochs: 16
|
||||
optimizer: adamw_bnb_8bit
|
||||
torchdistx_path:
|
||||
lr_scheduler: cosine
|
||||
learning_rate: 0.0001
|
||||
train_on_inputs: false
|
||||
group_by_length: true
|
||||
bf16: true
|
||||
fp16: false
|
||||
tf32: true
|
||||
gradient_checkpointing: true
|
||||
early_stopping_patience:
|
||||
resume_from_checkpoint:
|
||||
local_rank:
|
||||
logging_steps: 1
|
||||
xformers_attention: true
|
||||
flash_attention:
|
||||
gptq_groupsize:
|
||||
gptq_model_v1:
|
||||
warmup_steps: 100
|
||||
eval_steps: 17
|
||||
save_steps: 34
|
||||
load_best_model_at_end: false
|
||||
debug:
|
||||
deepspeed:
|
||||
weight_decay: 0.1
|
||||
fsdp:
|
||||
- full_shard
|
||||
- auto_wrap
|
||||
fsdp_config:
|
||||
fsdp_offload_params: true
|
||||
fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
|
||||
special_tokens:
|
||||
bos_token: "<s>"
|
||||
eos_token: "</s>"
|
||||
unk_token: "<unk>"
|
||||
|
||||
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generation_config.json
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{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 1,
|
||||
"eos_token_id": 2,
|
||||
"pad_token_id": 0,
|
||||
"transformers_version": "4.28.0.dev0"
|
||||
}
|
||||
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size 1996083
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||||
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||||
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||||
"model.layers.6.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.6.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.6.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.6.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
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||||
"model.layers.6.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.6.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.6.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.6.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
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||||
"model.layers.7.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.7.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.8.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
||||
"model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||
"model.norm.weight": "pytorch_model-00003-of-00003.bin"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
93385
tokenizer.json
Normal file
93385
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
33
tokenizer_config.json
Normal file
33
tokenizer_config.json
Normal file
@@ -0,0 +1,33 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"bos_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"model_max_length": 2048,
|
||||
"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user