tocmo0nlord/axolotl
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

more fixes

Browse Source
This commit is contained in:
Wing Lian
2023-05-14 09:16:41 -04:00
parent aef00b6c13
commit 42410c783c
1 changed files with 6 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
src/axolotl/utils/models.py
View File

@@ -184,7 +184,8 @@ def load_model(
for k, v in cfg.tokens.items(): for k, v in cfg.tokens.items():
tokenizer.add_special_tokens({k: v}) tokenizer.add_special_tokens({k: v})
model.resize_token_embeddings(len(tokenizer)) # this should only be needed if you are messing with new tokens in the vocab
# model.resize_token_embeddings(len(tokenizer))
if cfg.adapter and load_in_8bit and not cfg.load_4bit: if cfg.adapter and load_in_8bit and not cfg.load_4bit:
logging.info("converting PEFT model w/ prepare_model_for_int8_training") logging.info("converting PEFT model w/ prepare_model_for_int8_training")
@@ -207,7 +208,10 @@ def load_model(
m.scales = m.scales.half() m.scales = m.scales.half()
m.bias = m.bias.half() m.bias = m.bias.half()
if torch.cuda.device_count() > 1 and int(os.getenv("WORLD_SIZE", "1")) > 1: if torch.cuda.device_count() > 1 and int(os.getenv("WORLD_SIZE", "1")) > 1 and cfg.load_4bit:
# llama is PROBABLY model parallelizable, but the default isn't that it is
# so let's only set it for the 4bit, see
# https://github.com/johnsmith0031/alpaca_lora_4bit/blob/08b3fca4a4a9e0d3945be1bab4529f100a428636/finetune.py#L130-L133
model.is_parallelizable = True model.is_parallelizable = True
model.model_parallel = True model.model_parallel = True