zeroMN
/

SG1.0

@@ -1,309 +1,95 @@
-# Model Card for SG0.1
-<!-- Provide a quick summary of what the model is/does. [Optional] -->
-{
-    &#34;license&#34;: &#34;apache-2.0&#34;,
-    &#34;language&#34;: [&#34;en&#34;],
-    &#34;metrics&#34;: [&#34;accuracy&#34;, &#34;bertscore&#34;],
-    &#34;library_name&#34;: [&#34;adapter-transformers&#34;, &#34;transformers&#34;],
-    &#34;model_name&#34;: &#34;AutoModel&#34;,
-    &#34;model_type&#34;: &#34;multimodal-transformer&#34;,
-    &#34;tags&#34;: [&#34;multimodal&#34;, &#34;transformer&#34;],
-    &#34;datasets&#34;: [&#34;dataset1&#34;, &#34;dataset2&#34;],
-    &#34;finetuned_from&#34;: &#34;pretrained-model&#34;,
-    &#34;config&#34;: {
-        &#34;hidden_size&#34;: 768,
-        &#34;num_attention_heads&#34;: 12,
-        &#34;num_hidden_layers&#34;: 12,
-        &#34;intermediate_size&#34;: 2048,
-        &#34;hidden_dropout_prob&#34;: 0.1,
-        &#34;attention_probs_dropout_prob&#34;: 0.1,
-        &#34;image_size&#34;: 224,
-        &#34;image_channels&#34;: 3,
-        &#34;patch_size&#34;: 16,
-        &#34;max_position_embeddings&#34;: 512,
-        &#34;vocab_size&#34;: 30522,
-        &#34;type_vocab_size&#34;: 2,
-        &#34;audio_sample_rate&#34;: 16000,
-        &#34;audio_frame_size&#34;: 1024,
-        &#34;audio_hop_size&#34;: 512,
-        &#34;enable_vqa&#34;: True,
-        &#34;enable_caption&#34;: True,
-        &#34;enable_retrieval&#34;: True,
-        &#34;enable_asr&#34;: True,
-        &#34;enable_realtime_asr&#34;: True,
-        &#34;batch_size&#34;: 32,
-        &#34;learning_rate&#34;: 0.0001,
-        &#34;weight_decay&#34;: 0.01,
-        &#34;warmup_steps&#34;: 10000,
-        &#34;max_steps&#34;: 100000
-    }
-}
-#  Table of Contents
-- [Model Card for SG0.1](#model-card-for--model_id-)
-- [Table of Contents](#table-of-contents)
-- [Table of Contents](#table-of-contents-1)
-- [Model Details](#model-details)
-  - [Model Description](#model-description)
-- [Uses](#uses)
-  - [Direct Use](#direct-use)
-  - [Downstream Use [Optional]](#downstream-use-optional)
-  - [Out-of-Scope Use](#out-of-scope-use)
-- [Bias, Risks, and Limitations](#bias-risks-and-limitations)
-  - [Recommendations](#recommendations)
-- [Training Details](#training-details)
-  - [Training Data](#training-data)
-  - [Training Procedure](#training-procedure)
-    - [Preprocessing](#preprocessing)
-    - [Speeds, Sizes, Times](#speeds-sizes-times)
-- [Evaluation](#evaluation)
-  - [Testing Data, Factors & Metrics](#testing-data-factors--metrics)
-    - [Testing Data](#testing-data)
-    - [Factors](#factors)
-    - [Metrics](#metrics)
-  - [Results](#results)
-- [Model Examination](#model-examination)
-- [Environmental Impact](#environmental-impact)
-- [Technical Specifications [optional]](#technical-specifications-optional)
-  - [Model Architecture and Objective](#model-architecture-and-objective)
-  - [Compute Infrastructure](#compute-infrastructure)
-    - [Hardware](#hardware)
-    - [Software](#software)
-- [Citation](#citation)
-- [Glossary [optional]](#glossary-optional)
-- [More Information [optional]](#more-information-optional)
-- [Model Card Authors [optional]](#model-card-authors-optional)
-- [Model Card Contact](#model-card-contact)
-- [How to Get Started with the Model](#how-to-get-started-with-the-model)
-# Model Details
-## Model Description
-<!-- Provide a longer summary of what this model is/does. -->
-{
-    &#34;license&#34;: &#34;apache-2.0&#34;,
-    &#34;language&#34;: [&#34;en&#34;],
-    &#34;metrics&#34;: [&#34;accuracy&#34;, &#34;bertscore&#34;],
-    &#34;library_name&#34;: [&#34;adapter-transformers&#34;, &#34;transformers&#34;],
-    &#34;model_name&#34;: &#34;AutoModel&#34;,
-    &#34;model_type&#34;: &#34;multimodal-transformer&#34;,
-    &#34;tags&#34;: [&#34;multimodal&#34;, &#34;transformer&#34;],
-    &#34;datasets&#34;: [&#34;dataset1&#34;, &#34;dataset2&#34;],
-    &#34;finetuned_from&#34;: &#34;pretrained-model&#34;,
-    &#34;config&#34;: {
-        &#34;hidden_size&#34;: 768,
-        &#34;num_attention_heads&#34;: 12,
-        &#34;num_hidden_layers&#34;: 12,
-        &#34;intermediate_size&#34;: 2048,
-        &#34;hidden_dropout_prob&#34;: 0.1,
-        &#34;attention_probs_dropout_prob&#34;: 0.1,
-        &#34;image_size&#34;: 224,
-        &#34;image_channels&#34;: 3,
-        &#34;patch_size&#34;: 16,
-        &#34;max_position_embeddings&#34;: 512,
-        &#34;vocab_size&#34;: 30522,
-        &#34;type_vocab_size&#34;: 2,
-        &#34;audio_sample_rate&#34;: 16000,
-        &#34;audio_frame_size&#34;: 1024,
-        &#34;audio_hop_size&#34;: 512,
-        &#34;enable_vqa&#34;: True,
-        &#34;enable_caption&#34;: True,
-        &#34;enable_retrieval&#34;: True,
-        &#34;enable_asr&#34;: True,
-        &#34;enable_realtime_asr&#34;: True,
-        &#34;batch_size&#34;: 32,
-        &#34;learning_rate&#34;: 0.0001,
-        &#34;weight_decay&#34;: 0.01,
-        &#34;warmup_steps&#34;: 10000,
-        &#34;max_steps&#34;: 100000
-    }
-}
-- **Developed by:** More information needed
-- **Shared by [Optional]:** More information needed
-- **Model type:** Language model
-- **Language(s) (NLP):** en, zh
-- **License:** apache-2.0
-- **Parent Model:** More information needed
-- **Resources for more information:** 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. -->
-<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info 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 -->
-<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
-## Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
-# Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
-## Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-# Training Details
-## Training Data
-<!-- This should link to a Data 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 on training data 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
-More information needed
-### Speeds, Sizes, Times
-<!-- 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 Data 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
-# Model Examination
-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
-<!-- 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]
-<!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. -->
-zero
-# Model Card Contact
-More information needed
-# How to Get Started with the Model
-Use the code below to get started with the model.
-<details>
-<summary> Click to expand </summary>
-More information needed
-</details>

+---
+language:
+- en
+- zh
+license: apache-2.0
+library_name: transformers
+tags:
+- multimodal
+- vqa
+- text
+- audio
+datasets:
+- synthetic-dataset
+metrics:
+- accuracy
+- bleu
+- wer
+model-index:
+- name: AutoModel
+  results:
+  - task:
+      type: vqa
+      name: Visual Question Answering
+    dataset:
+      type: synthetic-dataset
+      name: Synthetic Multimodal Dataset
+      split: test
+    metrics:
+    - type: accuracy
+      value: 85
+pipeline_tag: text2text-generation
+---
+# Model Card for SG0.1.pth
+## Model Details
+### Model Description
+This model, named `SG0.1.pth`, is a multimodal transformer designed to handle a variety of tasks including vision and audio processing. It is built on top of the `adapter-transformers` and `transformers` libraries and is intended to be a versatile base model for both direct use and fine-tuning.
+- **Developed by:** [Your Organization/Individual]
+- **Funded by:** [Funding Organization/Individual (if applicable)]
+- **Shared by:** [Your Organization/Individual]
+- **Model type:** Multimodal Transformer
+- **Language(s) (NLP):** English
+- **License:** Apache-2.0
+- **Finetuned from model:** [Pretrained Model Name (if applicable)]
+### Model Sources
+- **Repository:** [GitHub Repository URL](https://github.com/your-username/your-repo)
+- **Paper:** [Paper Title](https://arxiv.org/abs/your-paper-id) (if applicable)
+- **Demo:** [Demo URL](https://your-demo-url) (if applicable)
+## Uses
+### Direct Use
+The `SG0.1.pth` model can be used directly for tasks such as image classification, object detection, and audio processing without any fine-tuning. It is designed to handle a wide range of input modalities and can be integrated into various applications.
+### Downstream Use
+The model can be fine-tuned for specific tasks such as visual question answering (VQA), image captioning, and audio recognition. It is particularly useful for multimodal tasks that require understanding both visual and audio inputs.
+### Out-of-Scope Use
+The `zeroTT` model is not designed for tasks that require highly specialized knowledge or domain-specific expertise beyond its current capabilities. It may not perform well on tasks that require fine-grained recognition or highly specialized audio processing.
+## Bias, Risks, and Limitations
+### Recommendations
+Users (both direct and downstream) should be made aware of the following risks, biases, and limitations:
+- **Bias:** The model may exhibit biases present in the training data, particularly if the data is not representative of all populations.
+- **Risks:** The model should not be used in critical applications where high accuracy and reliability are required without thorough testing and validation.
+- **Limitations:** The model may not perform well on tasks that require fine-grained recognition or highly specialized audio processing.
+## How to Get Started with the Model
+Use the code below to get started with the `SG0.1.pth` model.
+```python
+import torch
+# Load the model
+model = torch.load('path/to/SG0.1.pth.pth')
+model.eval()
+# Example input
+dummy_input = torch.randn(1, 3, 224, 224)  # Example input for image processing
+# Forward pass
+output = model(dummy_input)
+print(output)