Upload model

README.md

@@ -0,0 +1,199 @@
+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## 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]

config.json

@@ -0,0 +1,18 @@
+{
+  "architectures": [
+    "TimesformerScrollprizeModel"
+  ],
+  "auto_map": {
+    "AutoConfig": "timesformer_config.TimesformerScrollprizeConfig",
+    "AutoModel": "timesformer_model.TimesformerScrollprizeModel"
+  },
+  "depth": 8,
+  "dim": 512,
+  "n_heads": 6,
+  "num_classes": 16,
+  "num_frames": 26,
+  "patch_size": 16,
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.3",
+  "window_size": 64
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:490a98f9491e1180274ed3a0c0a9c611d73a0109c0e0c0fbba1097562a972488
+size 151853128

timesformer_config.py

@@ -0,0 +1,25 @@
+from transformers import PretrainedConfig
+
+
+class TimesformerScrollprizeConfig(PretrainedConfig):
+    # model_type = "timesformerscrollprize"
+
+    def __init__(
+        self,
+        window_size=64,
+        depth=8,
+        n_heads=6,
+        patch_size=16,
+        num_frames=26,
+        num_classes=16,
+        dim=512,
+        **kwargs,
+    ):
+        self.window_size=window_size
+        self.depth=depth
+        self.n_heads=n_heads
+        self.patch_size=patch_size
+        self.num_frames=num_frames
+        self.num_classes=num_classes
+        self.dim=dim
+        super().__init__(**kwargs)

timesformer_model.py

@@ -0,0 +1,33 @@
+from .timesformer_config import TimesformerScrollprizeConfig
+from transformers import PreTrainedModel
+import torch
+from timesformer_pytorch import TimeSformer
+
+# from .configuration_resnet import ResnetConfig
+
+
+
+
+class TimesformerScrollprizeModel(PreTrainedModel):
+    config_class = TimesformerScrollprizeConfig
+
+    def __init__(self, config):
+        super().__init__(config)
+        self.backbone=TimeSformer(
+                dim = config.dim,
+                image_size = config.window_size,
+                patch_size = config.patch_size,
+                num_frames = config.num_frames,
+                num_classes = config.num_classes,
+                channels=1,
+                depth = config.depth,
+                heads = config.n_heads,
+                dim_head =  64,
+                attn_dropout = 0.1,
+                ff_dropout = 0.1
+            )
+
+    def forward(self, tensor):
+        x = self.backbone(torch.permute(tensor, (0, 2, 1,3,4)))
+        x=x.view(-1,1,4,4)
+        return x