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license_link: LICENSE.md
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language:
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- en
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tags:
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- glm4
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- prism
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pipeline_tag: text-generation
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library_name: transformers
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---
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If you enjoy what we do, consider supporting us on Ko-fi! Every little bit means the world! https://ko-fi.com/ericelbaz
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<div align="center">
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<a href="https://ko-fi.com/ericelbaz#tier17681523526070">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63adf1fa42fd3b8dbaeb0c92/Qe17Xd59xWbucl1ZOl1jF.png" width="50%"/>
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<!--<span style="color:#e6edf3;font-size:18px;font-weight:600;">Complete both steps.</span>-->
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<!--<tr><td style="padding:6px 0;color:#e6edf3;font-size:13px;"><span style="color:#58a6ff;font-weight:600;margin-right:10px;">â‘ </span>Submit the access request form below</td></tr>-->
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<tr><td style="padding:6px 0;color:#e6edf3;font-size:13px;"><span style="color:#58a6ff;font-weight:600;margin-right:10px;">â‘¡</span>Support Donation Option:</td></tr>
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- **30B-A3B MoE Architecture** — Lightweight yet powerful Mixture-of-Experts model with 30 billion total parameters and ~3 billion active per token for fast, efficient inference
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- **128K Context Window** — Extended context for complex tasks and large codebases
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- **Interleaved & Preserved Thinking** — Multi-turn reasoning that persists across conversations with per-turn thinking control
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- **Strong In-Class Benchmarks** — 91.6% AIME 2025, 79.5% τ²-Bench, 59.2% SWE-bench Verified, 75.2% GPQA
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license_link: LICENSE.md
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language:
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- en
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- zh
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tags:
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- glm4
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- prism
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- moe
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pipeline_tag: text-generation
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library_name: transformers
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---
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# GLM-4.7-Flash-PRISM
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An unrestricted version of ZAI's GLM-4.7-Flash with over-refusal mechanisms removed using PRISM (Projected Refusal Isolation via Subspace Modification).
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<div align="center">
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### ☕ Support Our Work
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If you find this useful, consider supporting us on Ko-fi!
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[](https://ko-fi.com/ericelbaz)
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| Option | Description |
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|--------|-------------|
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| [**PRISM VIP Membership**](https://ko-fi.com/summary/6bae206c-a751-4868-8dc7-f531afd1fb4c) | Access to all PRISM models |
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| [**One-Time Support**](https://ko-fi.com/s/86882e8991) | Support this model |
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</div>
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---
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## Model Highlights
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- **PRISM Ablation** — State-of-the-art technique that removes over-refusal behaviors while preserving model capabilities
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- **30B-A3B MoE Architecture** — 30 billion total parameters with ~3 billion active per token for fast, efficient inference
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- **128K Context Window** — Extended context for complex tasks and large codebases
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- **Interleaved Thinking** — Multi-turn reasoning that persists across conversations with per-turn thinking control
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## Benchmarks
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| Benchmark | Score |
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|-----------|-------|
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| AIME 2025 | 91.6% |
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| τ²-Bench | 79.5% |
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| SWE-bench Verified | 59.2% |
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| GPQA | 75.2% |
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("Ex0bit/GLM-4.7-Flash-PRISM")
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tokenizer = AutoTokenizer.from_pretrained("Ex0bit/GLM-4.7-Flash-PRISM")
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```
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## License
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This model is released under the [PRISM Research License](LICENSE.md).
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