* Add examples of HF Agent * Modify folder structure and add link of demo.jpg * Fixes of readme * Merge applications and Applications
51 lines
1.9 KiB
Python
51 lines
1.9 KiB
Python
#
|
|
# Copyright 2016 The BigDL Authors.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
#
|
|
|
|
import argparse
|
|
|
|
from PIL import Image
|
|
from transformers import AutoTokenizer, LocalAgent
|
|
|
|
from bigdl.llm.transformers import AutoModelForCausalLM
|
|
|
|
if __name__ == "__main__":
|
|
parser = argparse.ArgumentParser(description="Run agent using vicuna model")
|
|
parser.add_argument("--repo-id-or-model-path", type=str, default="lmsys/vicuna-7b-v1.5",
|
|
help="The huggingface repo id for the Vicuna model to be downloaded"
|
|
", or the path to the huggingface checkpoint folder")
|
|
parser.add_argument("--image-path", type=str, default="demo.jpg",
|
|
help="Image to generate caption")
|
|
|
|
args = parser.parse_args()
|
|
model_path = args.repo_id_or_model_path
|
|
|
|
# Load model in 4 bit,
|
|
# which convert the relevant layers in the model into INT4 format
|
|
model = AutoModelForCausalLM.from_pretrained(model_path,
|
|
load_in_4bit=True)
|
|
# Load tokenizer
|
|
tokenizer = AutoTokenizer.from_pretrained(model_path)
|
|
# Load image
|
|
image = Image.open(args.image_path)
|
|
# Create an agent
|
|
agent = LocalAgent(model, tokenizer)
|
|
|
|
# Generate results
|
|
prompt = "Generate a caption for the 'image'"
|
|
print(f"Image path: {args.image_path}")
|
|
print('==', 'Prompt', '==')
|
|
print(prompt)
|
|
print(agent.run(prompt, image=image))
|