--- license: apache-2.0 datasets: - Mielikki/Erebus-87k - FourOhFour/Instruct_Phase - FourOhFour/RP_Phase - anthracite-core/full-opus-chosen-hermes-rejected-kto-v1 language: - en base_model: - IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml --- --- ### These are EXL2 quants for Aura-4B, Measurement file in the main branch, Check revisions for different BPW --- ## Aura-4B ![image/png](https://cdn-uploads.huggingface.co/production/uploads/626dfb8786671a29c715f8a9/jT4LeWC0ioarPieWtNZkE.png) ## Introduction **Aura-4B** is a state of the art dedicated roleplaying model designed to fulfill your every desire. This finetune has seen several hundreds of millions of tokens of completion, instruction and roleplaying data. A Kahneman-Tversky Optimization was applied to give this model a unique output style. Developed by **Aura Industries**, with contributions from **Anthracite Org** ## Model Details - **Model Name**: Aura-4B - **Base Model**: [IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml](https://huggingface.co/IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml) - **Model Type**: Chat Completions - **Prompt Format**: ChatML - **License**: Apache-2.0 - **Language**: English - **Max Context**: 8,192+ tokens ## License This model is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0). ## Quantizations [Static GGUF](https://huggingface.co/mradermacher/Aura-4B-GGUF) [Imatrix GGUF](https://huggingface.co/mradermacher/Aura-4B-i1-GGUF) EXL2 coming soon... # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Coming soon... | Metric |Value| |-------------------|----:| |Avg. | N/A| |IFEval (0-Shot) | N/A| |BBH (3-Shot) | N/A| |MATH Lvl 5 (4-Shot)| N/A| |GPQA (0-shot) | N/A| |MuSR (0-shot) | N/A| |MMLU-PRO (5-shot) | N/A| ## Training Configuration
Click here for Axolotl configs Completion SFT ```yaml base_model: IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: false strict: false hub_model_id: jeiku/completion4B hub_strategy: "all_checkpoints" push_dataset_to_hub: hf_use_auth_token: true datasets: - path: Mielikki/Erebus-87k type: completion field: body shuffle_merged_datasets: true val_set_size: 0.0025 output_dir: ./outputs/out adapter: lora_r: lora_alpha: lora_dropout: lora_target_linear: sequence_len: 8192 sample_packing: true eval_sample_packing: false pad_to_sequence_len: true plugins: - axolotl.integrations.liger.LigerPlugin liger_rope: true liger_rms_norm: true liger_swiglu: true liger_fused_linear_cross_entropy: true wandb_project: EXP4B wandb_entity: wandb_watch: wandb_name: EXP4B wandb_log_model: gradient_accumulation_steps: 12 micro_batch_size: 3 num_epochs: 1 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.00001 weight_decay: 0.05 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: true gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_ratio: 0.1 evals_per_epoch: 4 eval_table_size: eval_max_new_tokens: 128 saves_per_epoch: 1 debug: deepspeed: deepspeed_configs/zero3_bf16.json fsdp: fsdp_config: special_tokens: pad_token: <|finetune_right_pad_id|> ``` Instruct SFT ```yaml base_model: jeiku/completion4B model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: false strict: false hub_model_id: jeiku/instructered4B hub_strategy: "all_checkpoints" push_dataset_to_hub: hf_use_auth_token: true datasets: - path: FourOhFour/Instruct_Phase type: sharegpt conversation: chatml chat_template: chatml shuffle_merged_datasets: true val_set_size: 0.0025 output_dir: ./outputs/out adapter: lora_r: lora_alpha: lora_dropout: lora_target_linear: sequence_len: 8192 sample_packing: true eval_sample_packing: false pad_to_sequence_len: true plugins: - axolotl.integrations.liger.LigerPlugin liger_rope: true liger_rms_norm: true liger_swiglu: true liger_fused_linear_cross_entropy: true wandb_project: EXP4B wandb_entity: wandb_watch: wandb_name: EXP4B wandb_log_model: gradient_accumulation_steps: 12 micro_batch_size: 3 num_epochs: 2 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.00001 weight_decay: 0.05 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: true gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_ratio: 0.1 evals_per_epoch: 4 eval_table_size: eval_max_new_tokens: 128 saves_per_epoch: 2 debug: deepspeed: deepspeed_configs/zero3_bf16.json fsdp: fsdp_config: special_tokens: pad_token: <|finetune_right_pad_id|> ``` Roleplaying SFT ```yaml base_model: jeiku/instructered4B model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: false strict: false hub_model_id: jeiku/TheBest4B hub_strategy: "all_checkpoints" push_dataset_to_hub: hf_use_auth_token: true datasets: - path: FourOhFour/RP_Phase type: sharegpt conversation: chatml chat_template: chatml shuffle_merged_datasets: true val_set_size: 0.0025 output_dir: ./outputs/out adapter: lora_r: lora_alpha: lora_dropout: lora_target_linear: sequence_len: 8192 sample_packing: true eval_sample_packing: false pad_to_sequence_len: true plugins: - axolotl.integrations.liger.LigerPlugin liger_rope: true liger_rms_norm: true liger_swiglu: true liger_fused_linear_cross_entropy: true wandb_project: EXP4B wandb_entity: wandb_watch: wandb_name: EXP4B wandb_log_model: gradient_accumulation_steps: 12 micro_batch_size: 3 num_epochs: 2 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.00001 weight_decay: 0.05 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: true gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_ratio: 0.1 evals_per_epoch: 4 eval_table_size: eval_max_new_tokens: 128 saves_per_epoch: 2 debug: deepspeed: deepspeed_configs/zero3_bf16.json fsdp: fsdp_config: special_tokens: pad_token: <|finetune_right_pad_id|> ``` KTO ```yaml base_model: FourOhFour/Crispy_Crab_4B model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: false strict: false hub_model_id: jeiku/aura4bkto hub_strategy: "all_checkpoints" push_dataset_to_hub: hf_use_auth_token: true chat_template: chatml rl: kto rl_beta: 0.2 kto_desirable_weight: 0.2 datasets: - path: anthracite-core/full-opus-chosen-hermes-rejected-kto-v1 type: chatml.argilla shuffle_merged_datasets: true val_set_size: 0.0 output_dir: ./outputs/out sequence_len: 8192 sample_packing: false eval_sample_packing: false pad_to_sequence_len: false wandb_project: Aura-4B wandb_entity: wandb_watch: wandb_name: Aura-4B wandb_log_model: gradient_accumulation_steps: 16 micro_batch_size: 2 num_epochs: 2 max_steps: 500 optimizer: adamw_8bit lr_scheduler: cosine learning_rate: 0.00001 weight_decay: 0.05 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: true gradient_checkpointing: true gradient_checkpointing_kwargs: use_reentrant: true remove_unused_columns: false early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 10 evals_per_epoch: 2 eval_table_size: eval_max_new_tokens: saves_per_epoch: 1 debug: deepspeed: fsdp: fsdp_config: fsdp: fsdp_config: special_tokens: pad_token: <|finetune_right_pad_id|> ```