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@@ -16,6 +16,17 @@ base_model:
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  - **Attention Mechanism:** Hybrid sliding-window and full attention layers
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  - **Tokenizer:** Gemma tokenizer (vocab size 262,144)
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  ## Intended Use
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  - Designed for mathematical reasoning tasks, including problem solving, equation manipulation, and step-by-step derivations.
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  - Suitable for educational contexts, math tutoring, and research experiments in reasoning alignment.
 
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  - **Attention Mechanism:** Hybrid sliding-window and full attention layers
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  - **Tokenizer:** Gemma tokenizer (vocab size 262,144)
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+ ## Usage
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+ ```python
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+ from transformers import pipeline, TextStreamer
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+
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+ pipe = pipeline("text-generation", model="zai-org/GLM-4.7")
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+ messages = [
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+ {"role": "user", "content": "Who are you?"},
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+ ]
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+ streamer = TextStreamer(pipe.tokenizer)
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+ pipe(messages, streamer=streamer, max_new_tokens=10000)
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+ ```
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  ## Intended Use
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  - Designed for mathematical reasoning tasks, including problem solving, equation manipulation, and step-by-step derivations.
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  - Suitable for educational contexts, math tutoring, and research experiments in reasoning alignment.