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v9ai/salescue-triggers-v1
salescue-triggers-v1 is a text classification model from v9ai. Use it when you need a label for a piece of text. It is set up for salescue. The card lists the license as mit.
TemporalDisplacementModel module from the SalesCue sales intelligence library.
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From the Hugging Face model README
TemporalDisplacementModel module from the SalesCue sales intelligence library.
Status:
untrained— architecture only, random initialization. Use as a starting point for fine-tuning.
Temporal Displacement Model
Freshness isn't a classification — it's a continuous temporal reasoning task. TemporalDisplacementModel learns P(event_date | article_date, text_features), predicting when the event actually happened given how it's described. This models the relationship between event mention and event occurrence as a temporal displacement distribution.
from salescue import SalesCueModel
model = SalesCueModel.from_pretrained("v9ai/salescue-triggers-v1")
result = model.predict("your sales text here")
print(result)
new_fundingjob_changeexpansionlayoff_restructureacquisition_mergernew_product_launchleadership_changehiring_surgetechnology_adoptionactive_vendor_evaluationmicrosoft/deberta-v3-base (shared encoder, 768-dim)TemporalDisplacementModelmicrosoft/deberta-v3-base loaded via the SalesCue library.SalesCue is a sales intelligence library with 12 ML modules sharing a single DeBERTa-v3-base encoder backbone. Modules can be composed via Unix-style piping:
from salescue import Document
result = Document("interested in pricing") | ai.score | ai.intent | ai.sentiment
All modules: score intent reply triggers icp objection sentiment spam entities call subject emailgen
See the SalesCue documentation for details.