knowledgator/modern-gliner-bi-large-v1.0
Token Classification
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Updated
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22
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14
Text classification, relations extraction, NER, computational biology
#!pip install gliner -U
from gliner import GLiNER
model = GLiNER.from_pretrained("knowledgator/gliner-multitask-large-v0.5")
text = """
Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975 to develop and sell BASIC interpreters for the Altair 8800.
"""
labels = ["founder", "computer", "software", "position", "date"]
entities = model.predict_entities(text, labels)
for entity in entities:
print(entity["text"], "=>", entity["label"])
pip install gliner
from gliner import GLiNER
model = GLiNER.from_pretrained("knowledgator/gliner_small-v2.1")
prompt = """Find all positive aspects about the product:\n"""
text = """
I recently purchased the Sony WH-1000XM4 Wireless Noise-Canceling Headphones from Amazon and I must say, I'm thoroughly impressed. The package arrived in New York within 2 days, thanks to Amazon Prime's expedited shipping.
The headphones themselves are remarkable. The noise-canceling feature works like a charm in the bustling city environment, and the 30-hour battery life means I don't have to charge them every day. Connecting them to my Samsung Galaxy S21 was a breeze, and the sound quality is second to none.
I also appreciated the customer service from Amazon when I had a question about the warranty. They responded within an hour and provided all the information I needed.
However, the headphones did not come with a hard case, which was listed in the product description. I contacted Amazon, and they offered a 10% discount on my next purchase as an apology.
Overall, I'd give these headphones a 4.5/5 rating and highly recommend them to anyone looking for top-notch quality in both product and service.
"""
input_ = prompt+text
labels = ["match"]
matches = model.predict_entities(input_, labels)
for match in matches:
print(match["text"], "=>", match["score"])
from utca.core import (
AddData,
RenameAttribute,
Flush
)
from utca.implementation.predictors import (
TokenSearcherPredictor, TokenSearcherPredictorConfig
)
from utca.implementation.tasks import (
TokenSearcherNER,
TokenSearcherNERPostprocessor,
)
predictor = TokenSearcherPredictor(
TokenSearcherPredictorConfig(
device="cuda:0",
model="knowledgator/UTC-DeBERTa-base-v2"
)
)
ner_task = TokenSearcherNER(
predictor=predictor,
postprocess=[TokenSearcherNERPostprocessor(
threshold=0.5
)]
)
ner_task = TokenSearcherNER()
pipeline = (
AddData({"labels": ["scientist", "university", "city"]})
| ner_task
| Flush(keys=["labels"])
| RenameAttribute("output", "entities")
)
res = pipeline.run({
"text": """Dr. Paul Hammond, a renowned neurologist at Johns Hopkins University, has recently published a paper in the prestigious journal "Nature Neuroscience". """
})