LLaSM-Cllama2
Maintainer: LinkSoul
48
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
LLaSM-Cllama2 is a large language and speech model created by maintainer LinkSoul. It is based on the Chinese-Llama-2-7b and Baichuan-7B models, which are further fine-tuned and enhanced for speech-to-text capabilities. The model is capable of transcribing audio input and generating text responses.
Similar models include the Chinese-Llama-2-7b and Chinese-Llama-2-7b-4bit models, which are also created by LinkSoul and focused on Chinese language tasks. Another related model is the llama-3-chinese-8b-instruct-v3 from HFL, which is a large language model fine-tuned for instruction-following in Chinese.
Model inputs and outputs
LLaSM-Cllama2 takes audio input and generates text output. The audio input can be in various formats, and the model will transcribe the speech into text.
Inputs
- Audio file: The model accepts audio files as input, which can be in various formats such as MP3, WAV, or FLAC.
Outputs
- Transcribed text: The model outputs the transcribed text from the input audio.
Capabilities
LLaSM-Cllama2 is capable of accurately transcribing audio input into text, making it a useful tool for tasks such as speech-to-text conversion, audio transcription, and voice-based interaction. The model has been trained on a large amount of speech data and can handle a variety of accents, dialects, and speaking styles.
What can I use it for?
LLaSM-Cllama2 can be used for a variety of applications that involve speech recognition and text generation, such as:
- Automated transcription: Transcribing audio recordings, lectures, or interviews into text.
- Voice-based interfaces: Enabling users to interact with applications or devices using voice commands.
- Accessibility: Providing text-based alternatives for audio content, improving accessibility for users with hearing impairments.
- Language learning: Allowing users to practice their language skills by listening to and transcribing audio content.
Things to try
Some ideas for exploring the capabilities of LLaSM-Cllama2 include:
- Audio transcription: Try transcribing audio files in different languages, accents, and speaking styles to see how the model performs.
- Voice-based interaction: Experiment with using the model to control applications or devices through voice commands.
- Multilingual support: Investigate how the model handles audio input in multiple languages, as it claims to support both Chinese and English.
- Performance optimization: Explore the 4-bit version of the model to see if it can achieve similar accuracy with reduced memory and compute requirements.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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