starvector/starvector-8b-im2svg

README.md

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+---
+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

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+{
+  "_name_or_path": "ServiceNow/starvector-8b-im2svg",
+  "adapter_norm": "layer_norm",
+  "architectures": [
+    "StarVectorForCausalLM"
+  ],
+  "auto_map": {
+    "AutoConfig": "starvector_arch.StarVectorConfig",
+    "AutoModelForCausalLM": "starvector_arch.StarVectorForCausalLM"
+  },
+  "hidden_size": 4608,
+  "image_encoder_type": "siglip_384",
+  "image_size": 384,
+  "init_type": "normal",
+  "max_length_train": 16000,
+  "model_type": "starvector",
+  "num_attention_heads": 36,
+  "num_hidden_layers": 32,
+  "num_kv_heads": 4,
+  "starcoder_model_name": "bigcode/starcoder2-7b",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.40.1",
+  "use_cache": true,
+  "use_flash_attn": true,
+  "vocab_size": 49152
+}

model-00001-of-00004.safetensors

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model-00002-of-00004.safetensors

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model-00003-of-00004.safetensors

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model-00004-of-00004.safetensors

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starvector_arch.py

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+from transformers import (
+    PretrainedConfig,
+    PreTrainedModel
+)
+
+class StarVectorConfig(PretrainedConfig):
+    model_type = "starvector"
+
+    def __init__(
+        self,
+        starcoder_model_name: str = "bigcode/starcoderbase-1b",
+        image_encoder_type: str = "clip",
+        adapter_norm: str = "layer_norm",
+        image_size: int = 224,
+        max_length: int = 8192,
+        max_length_train: int = 8192,
+        use_flash_attn: bool = True,
+        use_cache: bool = True,
+        num_attention_heads: int = 16,
+        num_hidden_layers: int = 24,
+        vocab_size: int = 32000,
+        hidden_size: int = 1024,
+        num_kv_heads: int = 4,
+        **kwargs,
+    ):
+        self.starcoder_model_name = starcoder_model_name
+        self.image_encoder_type = image_encoder_type
+        self.adapter_norm = adapter_norm
+        self.image_size = image_size
+        self.max_length = max_length
+        self.max_length_train = max_length_train
+        self.use_flash_attn = use_flash_attn
+        self.use_cache = use_cache
+        self.num_attention_heads = num_attention_heads
+        self.num_hidden_layers = num_hidden_layers
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.num_kv_heads = num_kv_heads
+
+        super().__init__(**kwargs)
+
+class StarVectorForCausalLM(PreTrainedModel):
+    config_class = StarVectorConfig
+    _no_split_modules = []
+
+    def __init__(self, config: StarVectorConfig, **kwargs):
+        super().__init__(config)
+        starcoder_model_name = config.starcoder_model_name
+        if 'starcoder2' in starcoder_model_name:
+            from starvector.model.models.starvector_v2 import StarVectorStarCoder2
+            self.model = StarVectorStarCoder2(config=config, **kwargs)
+        else:
+            from starvector.model.models.starvector_v1 import StarVectorStarCoder
+            self.model = StarVectorStarCoder(config=config, **kwargs)
+
+    def forward(self, batch):
+        return self.model(batch)
+
+    def generate_im2svg(self, batch, **kwargs):
+        return self.model.generate_im2svg(batch, **kwargs)
+    
+    def generate_im2text(self, batch, **kwargs):
+        return self.model.generate_im2text(batch, **kwargs)
+
+    def process_images(self, images):
+        return self.model.image_encoder.process_images(images)
+