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fix quantified inference #302

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merged 5 commits into from
Sep 21, 2023
Merged

fix quantified inference #302

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bb783c3
Added a reply to saved_model size
iMountTai Sep 6, 2023
fa8a9f4
Merge branch 'ymcui:main' into main
iMountTai Sep 9, 2023
9d16973
update longbench score
iMountTai Sep 9, 2023
6e77320
Merge branch 'ymcui:main' into main
iMountTai Sep 21, 2023
07afe36
fix quantified inference
iMountTai Sep 21, 2023
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14 changes: 9 additions & 5 deletions scripts/inference/gradio_demo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -166,17 +166,21 @@ def setup():
if args.lora_model is None:
args.tokenizer_path = args.base_model
tokenizer = LlamaTokenizer.from_pretrained(args.tokenizer_path, legacy=True)
if args.load_in_4bit or args.load_in_8bit:
quantization_config = BitsAndBytesConfig(
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
bnb_4bit_compute_dtype=load_type,
)

base_model = LlamaForCausalLM.from_pretrained(
args.base_model,
torch_dtype=load_type,
low_cpu_mem_usage=True,
device_map='auto',
quantization_config=BitsAndBytesConfig(
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
bnb_4bit_compute_dtype=load_type
)
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
quantization_config=quantization_config if (args.load_in_4bit or args.load_in_8bit) else None
)

model_vocab_size = base_model.get_input_embeddings().weight.size(0)
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14 changes: 9 additions & 5 deletions scripts/inference/inference_hf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,17 +110,21 @@ def generate_prompt(instruction, system_prompt=DEFAULT_SYSTEM_PROMPT):
tokenizer = LlamaTokenizer.from_pretrained(args.tokenizer_path, legacy=True)
else:
tokenizer = LlamaTokenizer.from_pretrained(args.tokenizer_path, legacy=True)
if args.load_in_4bit or args.load_in_8bit:
quantization_config = BitsAndBytesConfig(
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
bnb_4bit_compute_dtype=load_type,
)

base_model = LlamaForCausalLM.from_pretrained(
args.base_model,
torch_dtype=load_type,
low_cpu_mem_usage=True,
device_map='auto',
quantization_config=BitsAndBytesConfig(
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
bnb_4bit_compute_dtype=load_type
)
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
quantization_config=quantization_config if (args.load_in_4bit or args.load_in_8bit) else None
)

model_vocab_size = base_model.get_input_embeddings().weight.size(0)
Expand Down
15 changes: 9 additions & 6 deletions scripts/openai_server_demo/openai_api_server.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,17 +69,20 @@
if args.lora_model is None:
args.tokenizer_path = args.base_model
tokenizer = LlamaTokenizer.from_pretrained(args.tokenizer_path, legacy=True)

if args.load_in_4bit or args.load_in_8bit:
quantization_config = BitsAndBytesConfig(
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
bnb_4bit_compute_dtype=load_type,
)
base_model = LlamaForCausalLM.from_pretrained(
args.base_model,
torch_dtype=load_type,
low_cpu_mem_usage=True,
device_map='auto' if not args.only_cpu else None,
quantization_config=BitsAndBytesConfig(
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
bnb_4bit_compute_dtype=load_type
)
load_in_4bit=args.load_in_4bit,
load_in_8bit=args.load_in_8bit,
quantization_config=quantization_config if (args.load_in_4bit or args.load_in_8bit) else None
)

model_vocab_size = base_model.get_input_embeddings().weight.size(0)
Expand Down