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Transformers
Safetensors
English
custom_model
multi-modal
conversational
speechllm
speech2text
custom_code
SpeechLLM / README.md
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metadata
language:
  - en
license: apache-2.0
library_name: transformers
tags:
  - multi-modal
  - conversational
  - speechllm
  - speech2text
datasets:
  - librispeech_asr
  - mozilla-foundation/common_voice_16_1
  - DynamicSuperb/EmotionalSpeechAudioClassification_RAVDESS-EmotionalSound
metrics:
  - wer

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Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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  • Model type: [More Information Needed]
  • Language(s) (NLP): English
  • License: Apache 2.0
  • Finetuned from model [optional]: HubertX and TinyLlama

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

# Load model directly from huggingface
from transformers import AutoModel
model = AutoModel.from_pretrained("shangeth/SpeechLLM", trust_remote_code=True)

model.generate_meta(
    audio_path="path-to-audio.wav", 
    instruction="Give me the following information about the audio [SpeechActivity, Transcript, Gender, Emotion, Age, Accent]",
    max_new_tokens=500, 
    return_special_tokens=False
)

# Model Generation
'''
{
  "SpeechActivity" : "True",
  "Transcript" : "Yes, I got it. I'll make the payment now.",
  "Gender" : "Female",
  "Emotion" : "Neutral",
  "Age" : "Young",
  "Accent" : "America",
}
'''

Training Details

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Evaluation

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Summary

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • Hardware Type: A100 80GB
  • Hours used: [More Information Needed]
  • Cloud Provider: E2E
  • Compute Region: India
  • Carbon Emitted: 1.73

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