| --- |
| license: cc-by-4.0 |
| language: |
| - hi |
| task_categories: |
| - automatic-speech-recognition |
| - text-generation |
| tags: |
| - hindi |
| - speech |
| - instruction-following |
| - llama-omni |
| - indic |
| pretty_name: Hindi LLaMA-Omni Instruct Dataset |
| size_categories: |
| - 100K<n<1M |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: |
| - "data/batch_0000[0-9][0-9]-*.parquet" |
| - "data/batch_0001[0-9][0-9]-*.parquet" |
| - "data/batch_000200-*.parquet" |
| - "data/batch_000201-*.parquet" |
| - "data/batch_000202-*.parquet" |
| - "data/batch_000203-*.parquet" |
| - "data/batch_000204-*.parquet" |
| - "data/batch_000205-*.parquet" |
| - "data/batch_000206-*.parquet" |
| - "data/batch_000207-*.parquet" |
| - "data/batch_000208-*.parquet" |
| - "data/batch_000209-*.parquet" |
| - "data/batch_000210-*.parquet" |
| - split: validation |
| path: |
| - "data/batch_000211-*.parquet" |
| - "data/batch_000212-*.parquet" |
| - "data/batch_000213-*.parquet" |
| - "data/batch_000214-*.parquet" |
| - "data/batch_000215-*.parquet" |
| - "data/batch_000216-*.parquet" |
| - "data/batch_000217-*.parquet" |
| - "data/batch_000218-*.parquet" |
| - "data/batch_000219-*.parquet" |
| - "data/batch_000220-*.parquet" |
| - "data/batch_000221-*.parquet" |
| - "data/batch_000222-*.parquet" |
| --- |
| |
| # Hindi LLaMA-Omni Instruct Dataset |
|
|
| A Hindi speech instruction-following dataset designed for training speech-language models such as [LLaMA-Omni](https://github.com/ictnlp/LLaMA-Omni). Each example pairs a spoken Hindi user question (audio) with a text assistant response. |
|
|
| --- |
|
|
| ## Dataset Summary |
|
|
| | Property | Value | |
| |---|---| |
| | Language | Hindi (hi) | |
| | Total examples | ~110,718 | |
| | Train split | ~105,000 examples (batches 001–210) | |
| | Validation split | ~5,500 examples (batches 211–222) | |
| | Audio format | FLAC, 16,000 Hz mono | |
| | Conversation type | Single-turn (one user question → one assistant response) | |
|
|
| --- |
|
|
| ## Data Sources |
|
|
| Text conversations are sourced from [ai4bharat/indic-instruct-data-v0.1](https://huggingface.co/datasets/ai4bharat/indic-instruct-data-v0.1), using the following subsets: |
|
|
| | Subset | Description | |
| |---|---| |
| | **Anudesh** | Human-annotated Hindi instruction-response pairs | |
| | **LMSYS** | Chat conversations translated/adapted to Hindi | |
| | **HH-RLHF** | Anthropic Helpful & Harmless RLHF data in Hindi | |
| | **Flan v2** | Flan collection prompts in Hindi | |
|
|
| Only **single-turn conversations** were retained (one user question, one assistant response). |
|
|
| --- |
|
|
| ## Audio Generation |
|
|
| User questions were converted to speech using: |
|
|
| - **TTS Model**: [`facebook/mms-tts-hin`](https://huggingface.co/facebook/mms-tts-hin) (MMS Hindi TTS — VITS architecture) |
| - **Sampling rate**: 16,000 Hz |
| - **Format**: FLAC (lossless) |
|
|
| Each audio file corresponds to the user turn of a conversation and is named `{id}-1_user.flac`. |
|
|
| --- |
|
|
| ## Dataset Structure |
|
|
| ### Parquet files (`data/`) |
|
|
| Each row in the parquet batches contains: |
|
|
| | Column | Type | Description | |
| |---|---|---| |
| | `id` | string | Unique conversation ID | |
| | `user_text` | string | Original Hindi text of the user question | |
| | `assistant_text` | string | Hindi text of the assistant response | |
| | `audio` | Audio | FLAC audio of the user question (`bytes` + `path`) | |
|
|
| ### JSON file (`dataset.json`) |
|
|
| A flat JSON array with the same conversations in message format: |
|
|
| ```json |
| { |
| "id": "c01d4234-8d55-51f5-b84f-0ddfd8a271b0", |
| "messages": [ |
| {"role": "user", "content": "न्यूयॉर्क में 3 दिवसीय यात्रा का कार्यक्रम बनाएं।"}, |
| {"role": "assistant", "content": "..."} |
| ] |
| } |
| ``` |
|
|
| --- |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("Pastaaaaa2003/hindi-llama-omni") |
| |
| # Access train split |
| for example in ds["train"]: |
| audio = example["audio"] # dict with 'bytes' and 'path' |
| question = example["user_text"] # Hindi text |
| answer = example["assistant_text"] |
| print(question, "->", answer[:80]) |
| ``` |
|
|
| --- |
|
|
| ## License |
|
|
| [Creative Commons Attribution 4.0 (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) |
|
|
| Please also comply with the licenses of the original source datasets: |
| - [ai4bharat/indic-instruct-data-v0.1](https://huggingface.co/datasets/ai4bharat/indic-instruct-data-v0.1) |
| - [facebook/mms-tts](https://huggingface.co/facebook/mms-tts) |
|
|
