Feature Extraction
Transformers
Safetensors
English
qwen2
Reasoning
Retrieval
text-embeddings-inference
Instructions to use Raderspace/RaDeR_Qwen25-14B_NuminaMath_MATH_allquerytypes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raderspace/RaDeR_Qwen25-14B_NuminaMath_MATH_allquerytypes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Raderspace/RaDeR_Qwen25-14B_NuminaMath_MATH_allquerytypes")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Raderspace/RaDeR_Qwen25-14B_NuminaMath_MATH_allquerytypes") model = AutoModel.from_pretrained("Raderspace/RaDeR_Qwen25-14B_NuminaMath_MATH_allquerytypes") - Notebooks
- Google Colab
- Kaggle
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README.md
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library_name: transformers
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license: mit
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---
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# Model Card for Model ID
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---
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library_name: transformers
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license: mit
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datasets:
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- Raderspace/MATH_NuminaMath_allquerytypes
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language:
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- en
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base_model:
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- Qwen/Qwen2.5-14B-Instruct
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tags:
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- Reasoning
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- Retrieval
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# Model Card for Model ID
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