ros/LLaMA-Factory
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

add export_device in webui #3333

Browse Source 
Former-commit-id: 30ebd3652809d73941e0a5e4a8be11d989faf98d
This commit is contained in:
hiyouga
2024-04-25 19:02:32 +08:00
parent 36be12a3b7
commit 9aeb88c426
7 changed files with 57 additions and 22 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
src/llmtuner/model/patcher.py
View File

@@ -12,7 +12,7 @@ from .utils.attention import configure_attn_implementation, print_attn_implement
from .utils.checkpointing import prepare_model_for_training
from .utils.embedding import resize_embedding_layer
from .utils.longlora import configure_longlora
from .utils.moe import add_z3_leaf_module
from .utils.moe import add_z3_leaf_module, configure_moe
from .utils.quantization import configure_quantization
from .utils.rope import configure_rope
@@ -46,17 +46,12 @@ def patch_config(
configure_rope(config, model_args, is_trainable)
configure_longlora(config, model_args, is_trainable)
configure_quantization(config, tokenizer, model_args, init_kwargs)
configure_moe(config, model_args, is_trainable)
if model_args.use_cache and not is_trainable:
setattr(config, "use_cache", True)
logger.info("Using KV cache for faster generation.")
if model_args.moe_aux_loss_coef is not None:
if getattr(config, "model_type", None) in ["mixtral", "qwen2_moe"]:
setattr(config, "router_aux_loss_coef", model_args.moe_aux_loss_coef)
elif getattr(config, "model_type", None) == "deepseek":
setattr(config, "aux_loss_alpha", model_args.moe_aux_loss_coef)
if getattr(config, "model_type", None) == "qwen":
setattr(config, "use_flash_attn", model_args.flash_attn)
for dtype_name, dtype in [("fp16", torch.float16), ("bf16", torch.bfloat16), ("fp32", torch.float32)]:
@@ -65,9 +60,6 @@ def patch_config(
if getattr(config, "model_type", None) == "qwen2" and is_trainable and model_args.flash_attn:
setattr(config, "use_cache", False) # qwen2 does not support use_cache when using flashattn
if getattr(config, "model_type", None) in ["mixtral", "qwen2_moe"] and is_trainable:
setattr(config, "output_router_logits", True)
init_kwargs["torch_dtype"] = model_args.compute_dtype
if not is_deepspeed_zero3_enabled():
init_kwargs["low_cpu_mem_usage"] = model_args.low_cpu_mem_usage