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fix lint (#2733)

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This commit is contained in:
Yineng Zhang
2025-01-05 14:45:42 +08:00
committed by GitHub
parent 3a22a303d1
commit bc6ad367c2
1 changed files with 12 additions and 13 deletions
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25
scripts/playground/reference_hf.py
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@@ -26,11 +26,12 @@ I'm going to the
import argparse import argparse
import requests import requests
from PIL import Image
import torch import torch
from PIL import Image
from transformers import ( from transformers import (
AutoModelForCausalLM, AutoProcessor, AutoModelForImageTextToText AutoModelForCausalLM,
AutoModelForImageTextToText,
AutoProcessor,
) )
from sglang.srt.hf_transformers_utils import get_tokenizer from sglang.srt.hf_transformers_utils import get_tokenizer
@@ -39,8 +40,7 @@ from sglang.srt.hf_transformers_utils import get_tokenizer
@torch.no_grad() @torch.no_grad()
def vlm_text_with_image(args): def vlm_text_with_image(args):
# Load the processor and model for ImageTextToText tasks # Load the processor and model for ImageTextToText tasks
processor = AutoProcessor.from_pretrained( processor = AutoProcessor.from_pretrained(args.model_path, trust_remote_code=True)
args.model_path, trust_remote_code=True)
model = AutoModelForImageTextToText.from_pretrained( model = AutoModelForImageTextToText.from_pretrained(
args.model_path, args.model_path,
torch_dtype=args.dtype, torch_dtype=args.dtype,
@@ -64,11 +64,8 @@ def vlm_text_with_image(args):
{ {
"type": "image", "type": "image",
}, },
{ {"type": "text", "text": "Describe this image."},
"type": "text", ],
"text": "Describe this image."
}
]
} }
] ]
@@ -84,11 +81,13 @@ def vlm_text_with_image(args):
if not hasattr(processor, "apply_chat_template"): if not hasattr(processor, "apply_chat_template"):
raise ValueError("The processor does not support chat templates.") raise ValueError("The processor does not support chat templates.")
text_prompt = processor.apply_chat_template( text_prompt = processor.apply_chat_template(
conversation, add_generation_prompt=True) conversation, add_generation_prompt=True
)
# Prepare inputs for the model # Prepare inputs for the model
inputs = processor(text=[text_prompt], images=[image], inputs = processor(text=[text_prompt], images=[image], return_tensors="pt").to(
return_tensors="pt").to("cuda:0") "cuda:0"
)
# Generate output from the model # Generate output from the model
output_ids = model.generate( output_ids = model.generate(