| | --- |
| | library_name: transformers |
| | tags: [] |
| | --- |
| | |
| | # Model Card for Model ID |
| |
|
| | <!-- Provide a quick summary of what the model is/does. --> |
| |
|
| | ## Code to create model |
| | ```py |
| | import torch |
| | from transformers import MimiConfig, MimiModel, AutoProcessor |
| | |
| | model_id = 'kyutai/mimi' |
| | config = MimiConfig.from_pretrained( |
| | model_id, |
| | intermediate_size=64, |
| | hidden_size=16, |
| | num_hidden_layers=2, |
| | num_key_value_heads=2, |
| | upsample_groups=16, |
| | num_filters=8, |
| | codebook_dim=8, |
| | vector_quantization_hidden_dimension=8, |
| | codebook_size=32, |
| | ) |
| | |
| | # Create model and randomize all weights |
| | model = MimiModel(config) |
| | |
| | torch.manual_seed(0) # Set for reproducibility |
| | for name, param in model.named_parameters(): |
| | param.data = torch.randn_like(param) |
| | |
| | processor = AutoProcessor.from_pretrained(model_id) |
| | ``` |
| |
|
| | ## ONNX conversion code |
| | ```py |
| | import torch |
| | import torch.nn as nn |
| | from transformers import MimiModel |
| | |
| | class MimiEncoder(nn.Module): |
| | def __init__(self, model): |
| | super(MimiEncoder, self).__init__() |
| | self.model = model |
| | |
| | def forward(self, input_values, padding_mask=None): |
| | return self.model.encode(input_values, padding_mask=padding_mask).audio_codes |
| | |
| | class MimiDecoder(nn.Module): |
| | def __init__(self, model): |
| | super(MimiDecoder, self).__init__() |
| | self.model = model |
| | |
| | def forward(self, audio_codes, padding_mask=None): |
| | return self.model.decode(audio_codes, padding_mask=padding_mask).audio_values |
| | |
| | model = MimiModel.from_pretrained("hf-internal-testing/tiny-random-MimiModel") |
| | encoder = MimiEncoder(model) |
| | decoder = MimiDecoder(model) |
| | |
| | dummy_encoder_inputs = torch.randn((5, 1, 82500)) |
| | torch.onnx.export( |
| | encoder, |
| | dummy_encoder_inputs, |
| | "encoder_model.onnx", |
| | export_params=True, |
| | opset_version=14, |
| | do_constant_folding=True, |
| | input_names=['input_values'], |
| | output_names=['audio_codes'], |
| | dynamic_axes={ |
| | 'input_values': {0: 'batch_size', 1: 'num_channels', 2: 'sequence_length'}, |
| | 'audio_codes': {0: 'batch_size', 2: 'codes_length'}, |
| | }, |
| | ) |
| | |
| | dummy_decoder_inputs = torch.randint(8, (4, 32, 91)) |
| | torch.onnx.export( |
| | decoder, |
| | dummy_decoder_inputs, |
| | "decoder_model.onnx", |
| | export_params=True, |
| | opset_version=14, |
| | do_constant_folding=True, |
| | input_names=['audio_codes'], |
| | output_names=['audio_values'], |
| | dynamic_axes={ |
| | 'audio_codes': {0: 'batch_size', 2: 'codes_length'}, |
| | 'audio_values': {0: 'batch_size', 1: 'num_channels', 2: 'sequence_length'}, |
| | }, |
| | ) |
| | ``` |
| |
|
| | ## Model Details |
| |
|
| | ### Model Description |
| |
|
| | <!-- Provide a longer summary of what this model is. --> |
| |
|
| | This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
| |
|
| | - **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] |
| |
|
| | ### 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 --> |
| |
|
| | [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] |
| |
|
| | ## Bias, Risks, and Limitations |
| |
|
| | <!-- This section is meant to convey both technical and sociotechnical limitations. --> |
| |
|
| | [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. |
| |
|
| | ## How to Get Started with the Model |
| |
|
| | Use the code below to get started with the model. |
| |
|
| | [More Information Needed] |
| |
|
| | ## Training Details |
| |
|
| | ### Training Data |
| |
|
| | <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
| |
|
| | [More Information Needed] |
| |
|
| | ### Training Procedure |
| |
|
| | <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
| |
|
| | #### Preprocessing [optional] |
| |
|
| | [More Information Needed] |
| |
|
| |
|
| | #### Training Hyperparameters |
| |
|
| | - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
| |
|
| | #### Speeds, Sizes, Times [optional] |
| |
|
| | <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
| |
|
| | [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. --> |
| |
|
| | **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] |
