Create README.md

README.md

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+---
+tags:
+- unsloth
+license: mit
+library_name: transformers
+base_model:
+- tngtech/DeepSeek-TNG-R1T2-Chimera
+pipeline_tag: text-generation
+---
+<div>
+<p style="margin-top: 0;margin-bottom: 0;">
+    <em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
+  </p>
+  <div style="display: flex; gap: 5px; align-items: center; ">
+    <a href="https://github.com/unslothai/unsloth/">
+      <img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
+    </a>
+    <a href="https://discord.gg/unsloth">
+      <img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
+    </a>
+    <a href="https://docs.unsloth.ai/">
+      <img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
+    </a>
+  </div>
+</div>
+
+# DeepSeek-TNG-R1T2-Chimera
+
+<div align="center">
+<img src="https://354918363417-runtime-assets.s3.eu-central-1.amazonaws.com/company_logo_light.svg"
+     alt="TNG Logo" 
+     width="400"
+     style="display: inline-block; vertical-align: middle;"/>
+</div>
+<br>
+<div align="center">
+  <a href="https://huggingface.co/tngtech/DeepSeek-TNG-R1T2-Chimera/blob/main/LICENSE.DeepSeek" style="margin: 2px;">
+    <img alt="License" src="https://img.shields.io/badge/License-MIT-f5de53?&color=f5de53" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+</div>
+<br>
+<div align="center">
+    <img alt="Intelligence Score" src="intelligence_score_vs_output_tokens.png" style="display: inline-block; vertical-align: middle;" width="750"/>
+</div>
+
+**Assembly of Experts Chimera model constructed with the DeepSeek [R1-0528](https://huggingface.co/deepseek-ai/DeepSeek-R1-0528), [R1](https://huggingface.co/deepseek-ai/DeepSeek-R1) and [V3-0324](https://huggingface.co/deepseek-ai/DeepSeek-V3-0324) parent models**
+
+We present our new **DeepSeek-TNG R1T2 Chimera** 671B model, the first successor to our original [*DeepSeek R1T Chimera*](https://huggingface.co/tngtech/DeepSeek-R1T-Chimera) that was released on April 26th. Unlike the original Chimera, which was based on the *two parent models* V3-0324 and R1, the new Chimera is a **Tri-Mind** *with three parents*, namely additionally R1-0528. It is constructed using the Assembly of Experts-method with relatively fine-granular direct brain edits. This more refined assembly allowed, among other improvements, the fixing of the &lt;think&gt; token consistency issue, which was a weakness of R1T and is now solved for R1T2. 
+
+**Sweet spot**
+
+R1T2 operates at a new sweet spot in intelligence vs. output token length. It appears to be...
+
+- about **20% faster than** the regular **R1**, and more than **twice as fast as R1-0528**
+- significantly **more intelligent than** the regular **R1** in benchmarks such as **GPQA** and **AIME-24**
+- much **more intelligent** and also **think-token consistent** compared to the first **R1T Chimera** 0426
+- and generally well-behaved and a **nice persona** to talk to, even without any system prompt.
+
+**Recommendations for your model decision**
+
+*R1T2* compared...
+- *vs R1:* We hope that R1T2 is a very desirable, almost universal **better and drop-in replacement for R1**
+- *vs R1-0528:* R1T2 is a much **cheaper alternative to full R1-0528**, if the fullest 0528-level intelligence is not required
+- *vs R1T:* R1T2 is usually **recommended over R1T**, unless the specific personality of R1T was optimal, the think-token issue not important, or R1T's higher speed crucial
+- *vs V3-0324:* V3 is so much faster that if you can live with the **lower intelligence, take V3**, however, if you **need reasoning, R1T2** is the go-to model
+
+**Limitations**
+
+- **R1-0528** is thinking much longer, but also is achieving **better hard benchmark results** than R1T2
+- As measured by SpeechMap.ai (courtesy of xlr8harder), **R1T2** is significantly **more reserved** than R1T, but not as much as R1-0528
+- Due to the influence of its R1 parent, which does not support function calling, **R1T2 is not yet recommended for function-calling** intensive applications at this stage (this may be fixed at a later stage)
+- When switching from R1T to R1T2 development, we changed from AIME24 and MT-Bench to AIME24, AIME25 and GPQA-Diamond for the intelligence score. With the new benchmark set, there is a larger score difference between R1 and the original R1T Chimera than published earlier.
+
+**Technological background**
+
+For details on the AoE construction process, you can read our [Paper on arXiV](https://arxiv.org/abs/2506.14794).
+
+
+## Model Details
+
+- **Architecture**: DeepSeek-MoE transformer-based language model
+- **Combination Method**: Assembly of Experts from the three DeepSeek parent models R1-0528, R1 and V3-0324
+- **Release Date**: 2025-07-02
+- **Design Team**: Robert Dahlke, Henrik Klagges, Benjamin Merkel, Fabian Klemm and David Reiss, Munich, Germany
+- **Extra Thanks**: Big thanks to DeepSeek for their great models and open-source generosity, and to the other researchers that have published on model merging methodologies.
+
+
+## Use, Out-of-scope Use, Other Limitations, Risks, Recommendations et al.
+Regarding the R1T/R1T2-Chimeras, we ask you to follow the careful guidelines that Microsoft has created for their "MAI-DS-R1" DeepSeek-based model. 
+These professional guidelines are available [here on Hugging Face](https://huggingface.co/microsoft/MAI-DS-R1).
+
+## EU AI Act
+
+Due to the strict new guidelines of the EU AI Act that take effect on August 2nd 2025, we recommend that each R1T/R1T2 user in the EU either familiarizes themselves with these requirements and assess their compliance, or ceases using the model in the EU after August 1st, 2025.
+
+## Contact, especially for your user feedback
+
+Please give us your feedback, especially if you find deficiencies in the model:
+- Email: [email protected]
+- X.com: @tngtech
+
+## Citation
+
+```
+@misc{tng_technology_consulting_gmbh_2025_07_0x,
+	author       = { TNG Technology Consulting GmbH },
+	title        = { DeepSeek-TNG-R1T2-Chimera },
+	year         = 2025,
+    month        = { July },
+	url          = { https://huggingface.co/tngtech/DeepSeek-TNG-R1T2-Chimera },
+	doi          = { xxx },
+	publisher    = { Hugging Face }
+}
+```