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README.md
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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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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.
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