Update README.md

README.md

@@ -1,78 +1,56 @@
 ---
-library_name: transformers
-tags: []
+license: cc-by-4.0
+datasets:
+- speechcolab/gigaspeech
+- parler-tts/mls_eng_10k
+- reach-vb/jenny_tts_dataset
+language:
+- en
+- hi
+base_model:
+- openai-community/gpt2
+pipeline_tag: text-to-speech
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
-
+Indri is a series of audio models that can do TTS, ASR, and audio continuation. This is the smallest model in our series and supports TTS tasks in 2 languages:
+1. English
+2. Hindi
 
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+`indri-0.1-125m-tts` is a novel, extremely small, and lightweight TTS model based on the transformer architecture.
+It models audio as tokens and can generate high-quality audio with consistent style cloning of the speaker.
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+### Key features
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+1. Based on GPT-2 architecture
+2. Supports voice cloning with small prompts
+3. Code mixing text input in 2 languages - English and Hindi
 
 ### Model Sources [optional]
 
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+- **Repository:** [https://github.com/cmeraki/indri]
+- **Demo:** [https://www.indrivoice.ai/]
 
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+## Technical details
 
-## Bias, Risks, and Limitations
+Please read our blog [here]() for more technical details on how it was built.
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+Here's a brief of how this model works:
 
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+1. Converts input text into tokens
+2. Runs autoregressive decoding on GPT-2 based transformer model and generates audio tokens
+3. Decodes audio tokens (from [Kyutaui/mimi](https://huggingface.co/kyutai/mimi)) to audio
 
 ## How to Get Started with the Model
 
 Use the code below to get started with the model.
 
-[More Information Needed]
-
 ## Training Details
 
 ### Training Data
@@ -100,74 +78,6 @@ Use the code below to get started with the model.
 
 [More Information Needed]
 
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
 ## Citation [optional]
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
@@ -175,25 +85,3 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 **BibTeX:**
 
 [More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]