wehub-resource-sync
25 lines
929 B
Python
25 lines
929 B
Python
|
|
""" This example illustrates how to use the slim-xsum model to provide 'extreme summarizations', generally
|
|
providing a headline or title (typically no more than 10-15 words) to describe a longer text passage. """
|
|
|
|
from llmware.models import ModelCatalog
|
|
|
|
slim_xsum_models = ["slim-xsum-tool", "slim-xsum-phi-3-gguf"]
|
|
|
|
# load the model
|
|
model = ModelCatalog().load_model("slim-xsum-phi-3-gguf",sample=False, temperature=0.0, max_output=200)
|
|
|
|
# load the test dataset packaged with the model (will be cached locally the first time you load)
|
|
test_set = ModelCatalog().get_test_script("slim-xsum-phi-3-gguf")
|
|
|
|
# iterate through the test set samples
|
|
for i, sample in enumerate(test_set):
|
|
|
|
# invoke function call on the model, and pass 'xsum' as the parameter
|
|
response = model.function_call(sample["context"], params=["xsum"])
|
|
|
|
# display the output
|
|
print("\nllm_response: ", i, response["llm_response"])
|
|
|
|
|