inital commit of things without the model

README.md

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+---
+datasets:
+- anon8231489123/ShareGPT_Vicuna_unfiltered
+- ehartford/wizard_vicuna_70k_unfiltered
+- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
+- QingyiSi/Alpaca-CoT
+- teknium/GPT4-LLM-Cleaned
+- teknium/GPTeacher-General-Instruct
+- metaeval/ScienceQA_text_only
+- hellaswag
+- tasksource/mmlu
+- openai/summarize_from_feedback
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Manticore 13B - Preview Release (previously Wizard Mega)
+
+Manticore 13B is a Llama 13B model fine-tuned on the following datasets:
+- [ShareGPT](https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered) - based on a cleaned and de-suped subset
+- [WizardLM](https://huggingface.co/datasets/ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered)
+- [Wizard-Vicuna](https://huggingface.co/datasets/ehartford/wizard_vicuna_70k_unfiltered)
+- [subset of QingyiSi/Alpaca-CoT for roleplay and CoT](https://huggingface.co/QingyiSi/Alpaca-CoT)
+- [GPT4-LLM-Cleaned](https://huggingface.co/datasets/teknium/GPT4-LLM-Cleaned)
+- [GPTeacher-General-Instruct](https://huggingface.co/datasets/teknium/GPTeacher-General-Instruct)
+- ARC-Easy & ARC-Challenge - instruct augmented  for detailed responses
+- mmlu: instruct augmented for detailed responses subset including
+  - abstract_algebra
+  - conceptual_physics
+  - formal_logic
+  - high_school_physics
+  - logical_fallacies
+- [hellaswag](https://huggingface.co/datasets/hellaswag) - 5K row subset of instruct augmented for concise responses
+- [metaeval/ScienceQA_text_only](https://huggingface.co/datasets/metaeval/ScienceQA_text_only) - instruct for concise responses
+- [openai/summarize_from_feedback](https://huggingface.co/datasets/openai/summarize_from_feedback) - instruct augmented tl;dr summarization
+
+
+# Demo
+
+Try out the model in HF Spaces. The demo uses a quantized GGML version of the model to quickly return predictions on smaller GPUs (and even CPUs). Quantized GGML may have some minimal loss of model quality.
+- https://huggingface.co/spaces/openaccess-ai-collective/manticore-ggml
+
+## Release Notes
+
+- https://wandb.ai/wing-lian/manticore-13b/runs/nq3u3uoh/workspace
+
+## Build
+
+Manticore was built with [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) on 8xA100 80GB 
+ - Preview Release: 1 epoch taking 8 hours. 
+ - The configuration to duplicate this build is provided in this repo's [/config folder](https://huggingface.co/openaccess-ai-collective/manticore-13b/tree/main/configs).
+
+## Bias, Risks, and Limitations
+Manticore 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).
+Manticore was fine-tuned from the base model LlaMa 13B, please refer to its model card's Limitations Section for relevant information.
+
+## Examples
+
+````
+### Instruction: write Python code that returns the first n numbers of the Fibonacci sequence using memoization.
+
+### Assistant: 
+````
+
+```
+### Instruction: Finish the joke, a mechanic and a car salesman walk into a bar...  
+
+### Assistant:
+```
+

config.json

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+{
+  "_name_or_path": "huggyllama/llama-13b",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "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": 0,
+  "rms_norm_eps": 1e-06,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.30.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

configs/manticore.yml

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+base_model: huggyllama/llama-13b
+# base_model: /workspace/manticore-13b/
+base_model_config: huggyllama/llama-13b
+model_type: LlamaForCausalLM
+tokenizer_type: LlamaTokenizer
+load_in_8bit: false
+datasets:
+  - path: winglian/evals
+    data_files:
+      - hf/ARC-Challenge.jsonl
+      - hf/ARC-Easy.jsonl
+      - mmlu/abstract_algebra.jsonl
+      - mmlu/conceptual_physics.jsonl
+      - mmlu/formal_logic.jsonl
+      - mmlu/high_school_physics.jsonl
+      - mmlu/logical_fallacies.jsonl
+    type: explainchoice
+  - path: winglian/evals
+    data_files:
+      - openai/tldr.jsonl
+    type: summarizetldr
+  - path: winglian/evals
+    data_files:
+      - hellaswag/hellaswag-concise.jsonl
+    type: concisechoice
+  - path: metaeval/ScienceQA_text_only
+    type: concisechoice
+  - path: ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
+    type: alpaca
+  - path: ehartford/wizard_vicuna_70k_unfiltered
+    type: sharegpt
+  - path: winglian/chatlogs-en-cleaned
+    data_files:
+      - sharegpt_cleaned.jsonl
+    type: sharegpt
+  - path: teknium/GPT4-LLM-Cleaned
+    type: alpaca
+  - path: teknium/GPTeacher-General-Instruct
+    data_files: gpt4-instruct-similarity-0.6-dataset.json
+    type: gpteacher
+  - path: QingyiSi/Alpaca-CoT
+    data_files:
+      - Chain-of-Thought/formatted_cot_data/aqua_train.json
+      - 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/gsm8k_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
+      - GPTeacher/Roleplay/formatted_roleplay-similarity_0.6-instruct-dataset.json
+    type: alpaca
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.02
+adapter:
+lora_model_dir:
+sequence_len: 2048
+max_packed_sequence_len: 2048
+lora_r:
+lora_alpha:
+lora_dropout:
+lora_target_modules:
+lora_fan_in_fan_out:
+wandb_project: manticore-13b
+wandb_watch:
+wandb_run_id:
+wandb_log_model:
+output_dir: ./manticore-13b
+batch_size: 512
+micro_batch_size: 8
+num_epochs: 4
+optimizer:
+torchdistx_path:
+lr_scheduler:
+learning_rate: 0.000032
+train_on_inputs: false
+group_by_length: false
+bf16: true
+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: 20
+eval_steps: 10
+save_steps:
+debug:
+deepspeed:
+weight_decay: 0
+fsdp:
+  - full_shard
+  - auto_wrap
+fsdp_config:
+  fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
+

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": "4.30.0.dev0"
+}

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special_tokens_map.json

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+    "rstrip": false,
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+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+}

tokenizer_config.json

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+    "rstrip": false,
+    "single_word": false
+  }
+}