AI Computer infrastructure for Bangla AI

Bangla AI needs the same accelerator fundamentals as global AI workloads, but local datasets, speech, OCR and language-model research create their own practical constraints. ComputeBD is designed around those local workflows.

COMMON WORKLOADS

Where AI Computer acceleration can help

  • Bangla LLM fine-tuning
  • Speech recognition and synthesis
  • Bangla OCR and document AI
  • Embeddings and semantic search
  • Research datasets and evaluation
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Ready-made notebooks for this

Shared by the ComputeBD team. Open one, change it to fit your work, then run it on an AI Computer — billed by the minute.

📓 Ready notebook

Whisper for Bangla & regional dialects

বাংলা ও আঞ্চলিক ভাষার জন্য Whisper

Fine-tune Whisper on FLEURS Bengali, then measure word error per region (Sylheti, Chittagong, Noakhali…).

Open this notebook ↗Read the short write-up →
📓 Ready notebook

Bangla dialect classifier (BanglaBERT)

আঞ্চলিক বাংলা চেনার ক্লাসিফায়ার (BanglaBERT)

Train a text classifier on the BD-Dialect dataset; compare standard Bangla BERT models and their licences.

Open this notebook ↗Read the short write-up →
📓 Ready notebook

Bangla text-to-speech (Indic Parler-TTS)

বাংলা টেক্সট-টু-স্পিচ (Indic Parler-TTS)

Turn Bangla text into natural speech with described voices — with a clear consent-first voice-cloning policy.

Open this notebook ↗Read the short write-up →
📓 Ready notebook

Cricket & talk-show sentiment

ক্রিকেট ও টক-শো সেন্টিমেন্ট

Build a Bangla sentiment dataset from commentary or talk-show transcripts and chart the mood minute by minute.

Open this notebook ↗Read the short write-up →
📓 Ready notebook

Ask questions of match & talk-show transcripts (RAG)

ম্যাচ ও টক-শোর ট্রান্সক্রিপ্টে প্রশ্ন (RAG)

Search transcripts by meaning and get Bangla answers that cite the minute they were said.

Open this notebook ↗Read the short write-up →
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