Create model_card.yaml

model_card.yaml

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+---
+language:
+  - en
+  - es
+  - fr
+  - de
+  - it
+  - pt
+  - nl
+  - ru
+  - zh
+  - ja
+  - ko
+  - ar
+  - multilingual
+license: apache-2.0
+library_name: transformers
+tags:
+  - text-generation
+  - image-text-to-text
+  - multimodal
+  - vision
+  - causal-lm
+  - long-context
+  - reasoning
+  - thinking
+  - conversational
+  - safe-ai
+  - 200k-context
+  - instruct
+  - chat
+  - llama
+  - llava
+  - function-calling
+  - tool-use
+  - structured-output
+  - json-mode
+  - ocr
+  - vqa
+  - visual-reasoning
+  - code-generation
+  - rag
+pipeline_tag: image-text-to-text
+datasets:
+  - common_crawl
+  - wikipedia
+  - books
+  - arxiv
+  - github
+  - stack_exchange
+  - laion
+  - coyo
+  - vqa-v2
+  - textvqa
+  - chartqa
+  - docvqa
+  - grit
+  - sharegpt
+model-index:
+  - name: Helion-V2.0-Thinking
+    results:
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: MMLU
+          type: mmlu
+        metrics:
+          - type: accuracy
+            value: 72.4
+            name: Accuracy
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: HellaSwag
+          type: hellaswag
+        metrics:
+          - type: accuracy
+            value: 84.3
+            name: Accuracy
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: ARC-Challenge
+          type: arc_challenge
+        metrics:
+          - type: accuracy
+            value: 68.9
+            name: Accuracy
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: TruthfulQA
+          type: truthful_qa
+        metrics:
+          - type: accuracy
+            value: 58.7
+            name: Accuracy
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: Winogrande
+          type: winogrande
+        metrics:
+          - type: accuracy
+            value: 79.2
+            name: Accuracy
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: GSM8K
+          type: gsm8k
+        metrics:
+          - type: accuracy
+            value: 64.8
+            name: Accuracy
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: HumanEval
+          type: humaneval
+        metrics:
+          - type: pass@1
+            value: 48.2
+            name: Pass@1
+      - task:
+          type: image-text-to-text
+          name: Visual Question Answering
+        dataset:
+          name: VQA v2
+          type: vqa_v2
+        metrics:
+          - type: accuracy
+            value: 89.2
+            name: Accuracy
+      - task:
+          type: image-text-to-text
+          name: Text-based VQA
+        dataset:
+          name: TextVQA
+          type: textvqa
+        metrics:
+          - type: accuracy
+            value: 76.8
+            name: Accuracy
+      - task:
+          type: image-text-to-text
+          name: Chart Question Answering
+        dataset:
+          name: ChartQA
+          type: chartqa
+        metrics:
+          - type: accuracy
+            value: 81.4
+            name: Accuracy
+      - task:
+          type: image-text-to-text
+          name: Document VQA
+        dataset:
+          name: DocVQA
+          type: docvqa
+        metrics:
+          - type: accuracy
+            value: 88.7
+            name: Accuracy
+      - task:
+          type: function-calling
+          name: Function Calling
+        dataset:
+          name: Berkeley Function Calling
+          type: bfcl
+        metrics:
+          - type: accuracy
+            value: 94.3
+            name: Accuracy
+      - task:
+          type: structured-output
+          name: Structured Output
+        dataset:
+          name: JSON Schema Adherence
+          type: json_schema
+        metrics:
+          - type: accuracy
+            value: 97.1
+            name: Accuracy
+base_model: llama
+model_type: llava
+inference: true
+widget:
+  - text: "Explain the theory of relativity in simple terms:"
+    example_title: "Science Explanation"
+  - text: "Write a short story about a robot learning to paint:"
+    example_title: "Creative Writing"
+  - text: "What objects are in this image?"
+    src: "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"
+    example_title: "Image Analysis"
+  - text: "Extract the text from this image:"
+    src: "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/docvqa_example.png"
+    example_title: "OCR Task"
+  - text: "Use the calculator tool to compute: (45 * 23) + 156"
+    example_title: "Tool Usage"
+---