qwerrwe / examples /llama-2 /gptq-lora.yml
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Add support for GPTQ using native transformers/peft (#468)
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base_model: TheBloke/Llama-2-7B-GPTQ
base_model_config: TheBloke/Llama-2-7B-GPTQ
is_llama_derived_model: false
gptq: true
gptq_bits: 4
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
tokenizer_use_fast: true
tokenizer_legacy: true
load_in_8bit: false
load_in_4bit: false
strict: false
push_dataset_to_hub:
hf_use_auth_token: true
datasets:
- path: mhenrichsen/alpaca_2k_test
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.01
adapter: lora
lora_model_dir:
sequence_len: 4096
sample_packing:
lora_r: 8
lora_alpha: 32
lora_dropout: 0.05
lora_target_modules:
- k_proj
- o_proj
- q_proj
- v_proj
lora_target_linear:
lora_fan_in_fan_out:
wandb_project:
wandb_watch:
wandb_run_id:
wandb_log_model:
output_dir: ./model-out
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_torch
adam_beta2: 0.95
adam_eps: 0.00001
max_grad_norm: 1.0
torchdistx_path:
lr_scheduler: cosine
lr_quadratic_warmup: true
learning_rate: 0.000017
train_on_inputs: false
group_by_length: false
bf16: false
fp16: false
float16: true
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention:
sdp_attention:
flash_optimum:
gptq_groupsize:
gptq_model_v1:
warmup_steps: 100
eval_steps:
save_steps:
debug:
deepspeed:
weight_decay: 0.1
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"