wehub-resource-sync
98 lines
4.1 KiB
Python
98 lines
4.1 KiB
Python
|
||
""" Starting with llmware 0.3.7, we have integrated support for OpenVino Generative models.
|
||
|
||
To get started:
|
||
|
||
`pip install openvino`
|
||
`pip install openvino_genai`
|
||
|
||
Openvino is supported on a wide range of platforms (including Windows, Linux, Mac OS), and is highly
|
||
optimized for Intel x86 architectures - both CPU and GPU.
|
||
|
||
The intent is for OpenVino models to be "drop in" replacements for Pytorch or GGUF models by simply
|
||
replacing the model with the OpenVino equivalent - usually indicated by an 'ov' at the end of the model name
|
||
|
||
"""
|
||
|
||
from llmware.models import ModelCatalog
|
||
|
||
from importlib import util
|
||
if not util.find_spec("openvino"):
|
||
print("\nto run this example, you need to install openvino first, e.g., pip3 install openvino")
|
||
|
||
if not util.find_spec("openvino_genai"):
|
||
print("\nto run this example, you need to install openvino_genai first, e.g., pip3 install openvino_genai")
|
||
|
||
|
||
# as of llmware 0.3.8, we have integrated the Model Depot collection into the default llmware model catalog
|
||
# please check out home page in Huggingface for a complete view of the collection
|
||
# https://www.huggingface.co/llmware
|
||
|
||
# to add your own OpenVino models, please see the example 'adding_openvino_or_onnx_model.py'
|
||
|
||
|
||
def getting_started():
|
||
|
||
model = ModelCatalog().load_model("bling-tiny-llama-ov", temperature=0.0, sample=False,
|
||
max_output=100)
|
||
|
||
query= "What was Microsoft's revenue in the 3rd quarter?"
|
||
|
||
context = ("Microsoft Cloud Strength Drives Third Quarter Results \nREDMOND, Wash. — April 25, 2023 — "
|
||
"Microsoft Corp. today announced the following results for the quarter ended March 31, 2023,"
|
||
" as compared to the corresponding period of last fiscal year:\n· Revenue was $52.9 billion"
|
||
" and increased 7% (up 10% in constant currency)\n· Operating income was $22.4 billion "
|
||
"and increased 10% (up 15% in constant currency)\n· Net income was $18.3 billion and "
|
||
"increased 9% (up 14% in constant currency)\n· Diluted earnings per share was $2.45 "
|
||
"and increased 10% (up 14% in constant currency).\n")
|
||
|
||
response = model.inference(query ,add_context=context)
|
||
|
||
print(f"\ngetting_started example - query - {query}")
|
||
print("getting_started example - response: ", response)
|
||
|
||
return response
|
||
|
||
|
||
def sentiment_analysis():
|
||
|
||
model = ModelCatalog().load_model("slim-sentiment-ov", temperature=0.0,sample=False)
|
||
|
||
text = ("The poor earnings results along with the worrisome guidance on the future has dampened "
|
||
"expectations and put a lot of pressure on the share price.")
|
||
|
||
response = model.function_call(text)
|
||
|
||
print(f"\nsentiment_analysis - {response}")
|
||
|
||
return response
|
||
|
||
|
||
def extract_info():
|
||
|
||
model = ModelCatalog().load_model("slim-extract-tiny-ov", temperature=0.0, sample=False)
|
||
|
||
text = ("Adobe shares tumbled as much as 11% in extended trading Thursday after the design software maker "
|
||
"issued strong fiscal first-quarter results but came up slightly short on quarterly revenue guidance. "
|
||
"Here’s how the company did, compared with estimates from analysts polled by LSEG, formerly known as Refinitiv: "
|
||
"Earnings per share: $4.48 adjusted vs. $4.38 expected Revenue: $5.18 billion vs. $5.14 billion expected "
|
||
"Adobe’s revenue grew 11% year over year in the quarter, which ended March 1, according to a statement. "
|
||
"Net income decreased to $620 million, or $1.36 per share, from $1.25 billion, or $2.71 per share, "
|
||
"in the same quarter a year ago. During the quarter, Adobe abandoned its $20 billion acquisition of "
|
||
"design software startup Figma after U.K. regulators found competitive concerns. The company paid "
|
||
"Figma a $1 billion termination fee.")
|
||
|
||
response = model.function_call(text,function="extract", params=["termination fee"])
|
||
|
||
print(f"\nextract_info - {response}")
|
||
|
||
return response
|
||
|
||
|
||
if __name__ == "__main__":
|
||
|
||
getting_started()
|
||
sentiment_analysis()
|
||
extract_info()
|
||
|