move unmaintained examples to archive (#2903) [skip ci]
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82
examples/archived/cerebras/btlm-ft.yml
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82
examples/archived/cerebras/btlm-ft.yml
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base_model: cerebras/btlm-3b-8k-base
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# optionally might have model_type or tokenizer_type
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model_type: AutoModelForCausalLM
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tokenizer_type: GPT2Tokenizer
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# Automatically upload checkpoint and final model to HF
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# hub_model_id: username/custom_model_name
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trust_remote_code: true
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tokenizer_use_fast: true
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tokenizer_legacy: true
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push_dataset_to_hub:
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hf_use_auth_token: true
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datasets:
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- path: mhenrichsen/alpaca_2k_test
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type: alpaca
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dataset_prepared_path: last_prepared_run
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val_set_size: 0.05
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adapter:
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lora_model_dir:
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sequence_len: 2048
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max_packed_sequence_len:
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sample_packing: false
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sample_packing_eff_est:
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sample_packing_seq_len_multiplier:
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total_num_tokens:
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lora_r:
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lora_alpha:
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lora_dropout:
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lora_target_modules:
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lora_target_linear:
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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output_dir: ./outputs/btlm-out
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gradient_accumulation_steps: 1
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micro_batch_size: 1
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num_epochs: 1
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optimizer: adamw_torch_fused
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adam_beta2: 0.95
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adam_eps: 0.000000001
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max_grad_norm: 1.0
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torchdistx_path:
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lr_scheduler: cosine
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lr_quadratic_warmup: true
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learning_rate: 0.000085
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train_on_inputs: true
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group_by_length: false
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bf16: auto
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tf32: true
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gradient_checkpointing: false
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resume_from_checkpoint:
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logging_steps: 1
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flash_attention: true
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sdp_attention:
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flash_optimum:
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gptq_groupsize:
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gptq_model_v1:
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warmup_steps: 32
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evals_per_epoch: 4
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saves_per_epoch: 1
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save_total_limit:
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weight_decay: 0.1
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special_tokens:
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pad_token: "<|endoftext|>"
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fsdp:
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# - full_shard
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# - auto_wrap
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fsdp_config:
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# fsdp_state_dict_type: FULL_STATE_DICT
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# fsdp_transformer_layer_cls_to_wrap: BTLMBlock
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51
examples/archived/cerebras/qlora.yml
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51
examples/archived/cerebras/qlora.yml
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base_model: cerebras/Cerebras-GPT-1.3B
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# Automatically upload checkpoint and final model to HF
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# hub_model_id: username/custom_model_name
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load_in_8bit: false
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load_in_4bit: true
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push_dataset_to_hub:
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datasets:
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- path: teknium/GPT4-LLM-Cleaned
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type: alpaca
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dataset_prepared_path:
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val_set_size: 0.05
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adapter: qlora
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lora_model_dir:
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sequence_len: 2048
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lora_r: 16
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lora_alpha: 32
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lora_dropout: 0.05
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lora_target_modules:
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- c_fc
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- c_attn
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- c_proj
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lora_target_linear:
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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output_dir: ./outputs/qlora-out
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batch_size: 4
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micro_batch_size: 4
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num_epochs: 2
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optimizer: paged_adamw_8bit
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torchdistx_path:
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lr_scheduler: cosine
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learning_rate: 0.0002
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bf16: auto
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tf32: true
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gradient_checkpointing: true
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention: true
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flash_attention:
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gptq_groupsize:
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gptq_model_v1:
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warmup_steps: 10
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evals_per_epoch: 4
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saves_per_epoch: 1
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weight_decay: 0.1
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special_tokens:
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pad_token: "<|endoftext|>"
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