Create README.md
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README.md
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---
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license: apache-2.0
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base_model: mistralai/Mistral-7B-v0.3
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tags:
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- generated_from_trainer
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- axolotl
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datasets:
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- cognitivecomputations/Dolphin-2.9
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- teknium/OpenHermes-2.5
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- m-a-p/CodeFeedback-Filtered-Instruction
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- cognitivecomputations/dolphin-coder
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- cognitivecomputations/samantha-data
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- microsoft/orca-math-word-problems-200k
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- Locutusque/function-calling-chatml
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- internlm/Agent-FLAN
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---
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# Dolphin 2.9.3 Mistral 7b v0.3 32k 🐬
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Curated and trained by Eric Hartford and Cognitive Computations
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[![Discord](https://img.shields.io/discord/1156064224225808488?logo=Discord&logoColor=%23ffffff&label=Discord&link=https%3A%2F%2Fdiscord.gg%2FtCMkMDDHwm)](https://discord.gg/cognitivecomputations)
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Discord: https://discord.gg/cognitivecomputations
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
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Our appreciation for the sponsors of Dolphin 2.9.3:
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- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xH100 node
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- [OnDemand](https://on-demand.io/) - provided inference sponsorship
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This model is based on mistralai/Mistral-7B-v0.3, and is governed by the apache 2.0 license.
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The base model has 32k context, and our finetuning took place with 8192 sequence length.
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Dolphin 2.9.3 uses ChatML prompt template format.
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example:
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```
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<|im_start|>system
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You are Dolphin, a helpful AI assistant.<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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```
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Dolphin-2.9.3 has a variety of instruction following, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
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Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
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Dolphin is licensed according to apache 2.0 license. We grant permission for any use, including commercial. Dolphin was trained on data generated from GPT4, among other models.
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## Evals
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/5KUgfzJyY1IM4Yg6bg3Dq.png)
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## Training
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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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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.0`
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```yaml
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base_model: mistralai/Mistral-7B-v0.3
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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load_in_8bit: false
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# load_in_4bit: true
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strict: false
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datasets:
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- path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/SystemChat_filtered_sharegpt.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/SystemChat_multilingual_sharegpt.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-translate-sharegpt2.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-codegen-sharegpt2.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/not_samantha_norefusals.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/Orca-Math-resort-unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/agent_instruct_react_unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/toolbench_instruct_j1s1_3k_unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/toolbench_negative_unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/toolbench_react_10p_unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/toolbench_tflan_cot_30p_unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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- path: /workspace/datasets/dolphin-2.9.3/openhermes200k_unfiltered.jsonl
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type: sharegpt
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conversation: chatml
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chat_template: chatml
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# adapter: qlora
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# lora_r: 128
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# lora_alpha: 16
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# lora_modules_to_save: [embed_tokens, lm_head]
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# lora_dropout: 0.05
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# lora_target_linear: true
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dataset_prepared_path: /workspace/axolotl/dolph-2.9.3-prepared
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val_set_size: 0.01
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output_dir: /workspace/axolotl/dolphin-2.9.3-mistral-7B
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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wandb_project: dolphin-2.9.3-Mistral-7B
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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gradient_accumulation_steps: 16
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micro_batch_size: 1
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num_epochs: 3
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optimizer: adamw_8bit
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lr_scheduler: cosine
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learning_rate: 5e-6
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32:
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 100
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# evals_per_epoch: 4
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eval_table_size:
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saves_per_epoch: 1
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save_total_limit: 2
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save_steps:
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debug:
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
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weight_decay: 0.1
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fsdp:
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fsdp_config:
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special_tokens:
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eos_token: "<|im_end|>"
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tokens:
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- "<|im_start|>"
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```
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