Text Classification
Transformers
Safetensors
English
bert
fill-mask
BERT
bert-mini
transformer
pre-training
nlp
tiny-bert
edge-ai
low-resource
micro-nlp
quantized
general-purpose
offline-assistant
intent-detection
real-time
embedded-systems
command-classification
voice-ai
eco-ai
english
lightweight
mobile-nlp
ner
semantic-search
contextual-ai
smart-devices
wearable-ai
privacy-first
text-embeddings-inference
Instructions to use boltuix/bert-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boltuix/bert-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boltuix/bert-mini")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("boltuix/bert-mini") model = AutoModelForMaskedLM.from_pretrained("boltuix/bert-mini") - Notebooks
- Google Colab
- Kaggle
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- π¬ [Support & Community](#support--community)
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# π§ bert-mini β Lightweight BERT for Edge AI, IoT & On-Device NLP π
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β‘ Built for low-latency, lightweight NLP tasks β perfect for smart assistants, microcontrollers, and embedded apps!
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- π [Credits](#credits)
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- π¬ [Support & Community](#support--community)
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## Overview
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