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v9ai/salescue-intent-v1
salescue-intent-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.
NeuralHawkesIntentPredictor module from the SalesCue sales intelligence library.
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From the Hugging Face model README
NeuralHawkesIntentPredictor module from the SalesCue sales intelligence library.
Status:
untrained— architecture only, random initialization. Use as a starting point for fine-tuning.
Neural Hawkes Process for Buying Journey
Models the prospect's buying journey as a marked temporal point process where each signal (event) has a type (mark) and arrival time. The intensity function of future events depends on the history of past events via a neural Hawkes process. This directly models the self-exciting property of buying behavior: interest begets more interest.
from salescue import SalesCueModel
model = SalesCueModel.from_pretrained("v9ai/salescue-intent-v1")
result = model.predict("your sales text here")
print(result)
unawareawareresearchingevaluatingcommittedpurchasingmicrosoft/deberta-v3-base (shared encoder, 768-dim)NeuralHawkesIntentPredictormicrosoft/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.