Update README.md

README.md

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 license: mit
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+
+GigaBind
+
+A finetuned ImageBind using Lora for images, audio, and many many other modalitiesi
+
+
+
+
+
+
+## Usage
+```python
+import logging
+import torch
+import data
+
+from models import imagebind_model
+from models.imagebind_model import ModalityType, load_module
+from models import lora as LoRA
+
+logging.basicConfig(level=logging.INFO, force=True)
+
+
+lora = True
+linear_probing = False
+device = "cpu"  # "cuda:0" if torch.cuda.is_available() else "cpu"
+load_head_post_proc_finetuned = True
+
+assert not (linear_probing and lora), \
+            "Linear probing is a subset of LoRA training procedure for ImageBind. " \
+            "Cannot set both linear_probing=True and lora=True. "
+
+if lora and not load_head_post_proc_finetuned:
+    # Hack: adjust lora_factor to the `max batch size used during training / temperature` to compensate missing norm
+    lora_factor = 12 / 0.07
+else:
+    # This assumes proper loading of all params but results in shift from original dist in case of LoRA
+    lora_factor = 1
+
+text_list=["bird",
+           "car",
+           "dog3",
+           "dog5",
+           "dog8",
+           "grey_sloth_plushie"]
+image_paths=[".assets/bird_image.jpg",
+             ".assets/car_image.jpg",
+             ".assets/dog3.jpg",
+             ".assets/dog5.jpg",
+             ".assets/dog8.jpg",
+             ".assets/grey_sloth_plushie.jpg"]
+audio_paths=[".assets/bird_audio.wav",
+             ".assets/car_audio.wav",
+             ".assets/dog_audio.wav"]
+
+# Instantiate model
+model = imagebind_model.imagebind_huge(pretrained=True)
+if lora:
+    model.modality_trunks.update(
+        LoRA.apply_lora_modality_trunks(model.modality_trunks, rank=4,
+                                        layer_idxs={ModalityType.TEXT: [0, 1, 2, 3, 4, 5, 6, 7, 8],
+                                                    ModalityType.VISION: [0, 1, 2, 3, 4, 5, 6, 7, 8]},
+                                        modality_names=[ModalityType.TEXT, ModalityType.VISION]))
+
+    # Load LoRA params if found
+    LoRA.load_lora_modality_trunks(model.modality_trunks,
+                                   checkpoint_dir=".checkpoints/lora/550_epochs_lora", postfix="_dreambooth_last")
+
+    if load_head_post_proc_finetuned:
+        # Load postprocessors & heads
+        load_module(model.modality_postprocessors, module_name="postprocessors",
+                    checkpoint_dir=".checkpoints/lora/550_epochs_lora", postfix="_dreambooth_last")
+        load_module(model.modality_heads, module_name="heads",
+                    checkpoint_dir=".checkpoints/lora/550_epochs_lora", postfix="_dreambooth_last")
+elif linear_probing:
+    # Load heads
+    load_module(model.modality_heads, module_name="heads",
+                checkpoint_dir="./.checkpoints/lora/500_epochs_lp", postfix="_dreambooth_last")
+
+model.eval()
+model.to(device)
+
+# Load data
+inputs = {
+    ModalityType.TEXT: data.load_and_transform_text(text_list, device),
+    ModalityType.VISION: data.load_and_transform_vision_data(image_paths, device, to_tensor=True),
+    ModalityType.AUDIO: data.load_and_transform_audio_data(audio_paths, device),
+}
+
+with torch.no_grad():
+    embeddings = model(inputs)
+
+print(
+    "Vision x Text: ",
+    torch.softmax(embeddings[ModalityType.VISION] @ embeddings[ModalityType.TEXT].T * (lora_factor if lora else 1), dim=-1),
+)
+print(
+    "Audio x Text: ",
+    torch.softmax(embeddings[ModalityType.AUDIO] @ embeddings[ModalityType.TEXT].T * (lora_factor if lora else 1), dim=-1),
+)
+print(
+    "Vision x Audio: ",
+    torch.softmax(embeddings[ModalityType.VISION] @ embeddings[ModalityType.AUDIO].T, dim=-1),
+)
+```
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+