add support for trust_remote_code for mpt models
Browse files- examples/mpt-7b/README.md +6 -0
- examples/mpt-7b/config.yml +59 -0
- src/axolotl/utils/models.py +3 -0
examples/mpt-7b/README.md
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# MPT-7B
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```shell
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accelerate launch scripts/finetune.py examples/mpt-7b/config.yml
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```
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examples/mpt-7b/config.yml
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base_model: mosaicml/mpt-7b
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base_model_config: mosaicml/mpt-7b
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model_type: AutoModelForCausalLM
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tokenizer_type: GPTNeoXTokenizer
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trust_remote_code: true # required for mpt as their model class is not merged into transformers yet
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load_in_8bit: false
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datasets:
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- path: vicgalle/alpaca-gpt4
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.02
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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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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_modules:
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- q_proj
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- v_proj
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lora_fan_in_fan_out: false
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wandb_project: mpt-alpaca-7b
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wandb_watch:
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wandb_run_id:
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wandb_log_model: checkpoint
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output_dir: ./mpt-alpaca-7b
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batch_size: 4
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micro_batch_size: 1
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num_epochs: 3
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optimizer: adamw_bnb_8bit
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torchdistx_path:
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lr_scheduler: cosine
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learning_rate: 0.0000002
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train_on_inputs: false
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group_by_length: false
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bf16: true
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tf32: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 5
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xformers_attention:
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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: 20
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eval_steps: 110
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save_steps: 660
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debug:
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deepspeed:
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weight_decay: 0.0001
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: "<|padding|>"
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bos_token: "<|endoftext|>"
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eos_token: "<|endoftext|>"
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unk_token: "<|endoftext|>"
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src/axolotl/utils/models.py
CHANGED
@@ -113,6 +113,7 @@ def load_model(
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load_in_8bit=cfg.load_in_8bit and cfg.adapter is not None,
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torch_dtype=torch_dtype,
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device_map=cfg.device_map,
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)
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else:
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model = AutoModelForCausalLM.from_pretrained(
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load_in_8bit=cfg.load_in_8bit and cfg.adapter is not None,
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torch_dtype=torch_dtype,
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device_map=cfg.device_map,
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)
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except Exception as e:
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logging.error(
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load_in_8bit=cfg.load_in_8bit and cfg.adapter is not None,
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torch_dtype=torch_dtype,
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device_map=cfg.device_map,
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)
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if not tokenizer:
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load_in_8bit=cfg.load_in_8bit and cfg.adapter is not None,
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torch_dtype=torch_dtype,
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device_map=cfg.device_map,
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trust_remote_code=True if cfg.trust_remote_code is True else False,
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)
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else:
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model = AutoModelForCausalLM.from_pretrained(
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load_in_8bit=cfg.load_in_8bit and cfg.adapter is not None,
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torch_dtype=torch_dtype,
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device_map=cfg.device_map,
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trust_remote_code=True if cfg.trust_remote_code is True else False,
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)
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except Exception as e:
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logging.error(
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load_in_8bit=cfg.load_in_8bit and cfg.adapter is not None,
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torch_dtype=torch_dtype,
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device_map=cfg.device_map,
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trust_remote_code=True if cfg.trust_remote_code is True else False,
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)
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if not tokenizer:
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