Add pipeline tag and library name to metadata

#6
by nielsr HF Staff - opened
Files changed (1) hide show
  1. README.md +6 -6
README.md CHANGED
@@ -1,7 +1,9 @@
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  ---
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- license: apache-2.0
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  base_model:
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- - stepfun-ai/Step3-VL-10B-Base
 
 
 
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  ---
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  <div align="center">
@@ -57,8 +59,6 @@ STEP3-VL-10B delivers best-in-class performance across major multimodal benchmar
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  | **HMMT 2025** | 78.18 | **92.14** | 57.29 | 67.71 | 65.68 | 51.30 |
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  | **LiveCodeBench** | 75.77 | **76.43** | 48.71 | 69.45 | 72.01 | 57.10 |
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- <!-- > **Note:** **SeRe** (Sequential Reasoning) uses a max length of 64K tokens; **PaCoRe** (Parallel Coordinated Reasoning) synthesizes 16 SeRe rollouts with a max length of 128K tokens. -->
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-
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  > **Note on Inference Modes:**
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  >
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  > **SeRe (Sequential Reasoning):** The standard inference mode using sequential generation (Chain-of-Thought) with a max length of 64K tokens.
@@ -120,7 +120,7 @@ STEP3-VL-10B delivers best-in-class performance across major multimodal benchmar
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  ### Inference with Hugging Face Transformers
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- We introduce how to use our model at inference stage using transformers library. It is recommended to use python=3.10, torch>=2.1.0, and transformers=4.57.0 as the development environment.We currently only support bf16 inference, and multi-patch for image preprocessing is supported by default. This behavior is aligned with vllm and sglang.
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  ```python
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  from transformers import AutoProcessor, AutoModelForCausalLM
@@ -185,4 +185,4 @@ If you find this project useful in your research, please cite our technical repo
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  ## 📄 License
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- This project is open-sourced under the [Apache 2.0 License](https://www.google.com/search?q=LICENSE).
 
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  ---
 
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  base_model:
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+ - stepfun-ai/Step3-VL-10B-Base
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+ license: apache-2.0
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+ library_name: transformers
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+ pipeline_tag: image-text-to-text
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  ---
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  <div align="center">
 
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  | **HMMT 2025** | 78.18 | **92.14** | 57.29 | 67.71 | 65.68 | 51.30 |
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  | **LiveCodeBench** | 75.77 | **76.43** | 48.71 | 69.45 | 72.01 | 57.10 |
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  > **Note on Inference Modes:**
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  >
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  > **SeRe (Sequential Reasoning):** The standard inference mode using sequential generation (Chain-of-Thought) with a max length of 64K tokens.
 
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  ### Inference with Hugging Face Transformers
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+ We introduce how to use our model at inference stage using transformers library. It is recommended to use python=3.10, torch>=2.1.0, and transformers=4.57.0 as the development environment. We currently only support bf16 inference, and multi-patch for image preprocessing is supported by default. This behavior is aligned with vllm and sglang.
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  ```python
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  from transformers import AutoProcessor, AutoModelForCausalLM
 
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  ## 📄 License
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+ This project is open-sourced under the [Apache 2.0 License](https://www.google.com/search?q=LICENSE).