Update README.md

README.md

@@ -15,6 +15,7 @@ tags:
 - 8-bit
 - GGUF
 - text-generation
+license: apache-2.0
 ---
 # [MaziyarPanahi/Trinity-Mini-GGUF](https://huggingface.co/MaziyarPanahi/Trinity-Mini-GGUF)
 - Model creator: [arcee-ai](https://huggingface.co/arcee-ai)
@@ -42,4 +43,123 @@ Here is an incomplete list of clients and libraries that are known to support GG
 
 ## Special thanks
 
-🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.
+🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.
+
+
+Original README:
+
+---
+
+<div align="center">
+  <picture>
+    <img
+      src="https://cdn-uploads.huggingface.co/production/uploads/6435718aaaef013d1aec3b8b/i-v1KyAMOW_mgVGeic9WJ.png"
+      alt="Arcee Trinity Mini"
+      style="max-width: 100%; height: auto;"
+    >
+  </picture>
+</div>
+
+# Trinity Mini GGUF
+
+Trinity Mini is an Arcee AI 26B MoE model with 3B active parameters. It is the medium-sized model in our new Trinity family, a series of open-weight models for enterprise and tinkerers alike.
+
+This model is tuned for reasoning, but in testing, it uses a similar total token count to competitive instruction-tuned models.
+
+These are the GGUF files for running on llama.cpp powered platforms
+
+***
+
+Trinity Mini is trained on 10T tokens gathered and curated through a key partnership with [Datology](https://www.datologyai.com/), building upon the excellent dataset we used on [AFM-4.5B](https://huggingface.co/arcee-ai/AFM-4.5B) with additional math and code.
+
+Training was performed on a cluster of 512 H200 GPUs powered by [Prime Intellect](https://www.primeintellect.ai/) using HSDP parallelism.
+
+More details, including key architecture decisions, can be found on our blog [here](https://www.arcee.ai/blog/the-trinity-manifesto)
+
+Try it out now at [chat.arcee.ai](http://chat.arcee.ai/)
+
+***
+
+## Model Details
+
+* **Model Architecture:** AfmoeForCausalLM
+* **Parameters:** 26B, 3B active
+* **Experts:** 128 total, 8 active, 1 shared
+* **Context length:** 128k
+* **Training Tokens:** 10T
+* **License:** [Apache 2.0](https://huggingface.co/arcee-ai/Trinity-Mini#license)
+* **Recommended settings:**
+    * temperature: 0.15
+    * top_k: 50
+    * top_p: 0.75
+    * min_p: 0.06
+
+***
+
+## Benchmarks
+
+![](https://cdn-uploads.huggingface.co/production/uploads/6435718aaaef013d1aec3b8b/UMV0OZh_H1JfvgzBTXh6u.png)
+
+<div align="center">
+  <picture>
+      <img src="https://cdn-uploads.huggingface.co/production/uploads/6435718aaaef013d1aec3b8b/sSVjGNHfrJKmQ6w8I18ek.png" style="background-color:ghostwhite;padding:5px;" width="17%" alt="Powered by Datology">
+  </picture>
+</div>
+
+### Running our model
+
+- [llama.cpp](https://huggingface.co/arcee-ai/Trinity-Mini#llamacpp)
+- [LM Studio](https://huggingface.co/arcee-ai/Trinity-Mini#lm-studio)
+- [API](https://huggingface.co/arcee-ai/Trinity-Mini#api)
+
+## llama.cpp
+
+Supported in llama.cpp release b7061
+
+Download the latest [llama.cpp release](https://github.com/ggml-org/llama.cpp/releases)
+
+```
+llama-server -hf arcee-ai/Trinity-Mini-GGUF:q4_k_m \
+  --temp 0.15 \
+  --top-k 50 \
+  --top-p 0.75
+  --min-p 0.06
+```
+
+## LM Studio
+
+Supported in latest LM Studio runtime
+
+Update to latest available, then verify your runtime by:
+
+1. Click "Power User" at the bottom left
+2. Click the green "Developer" icon at the top left
+3. Select "LM Runtimes" at the top
+4. Refresh the list of runtimes and verify that the latest is installed
+
+Then, go to Model Search and search for `arcee-ai/Trinity-Mini-GGUF`, download your prefered size, and load it up in the chat
+
+## API
+
+Trinity Mini is available today on openrouter:
+
+https://openrouter.ai/arcee-ai/trinity-mini
+
+```
+curl -X POST "https://openrouter.ai/v1/chat/completions" \
+  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "arcee-ai/trinity-mini",
+    "messages": [
+      {
+        "role": "user",
+        "content": "What are some fun things to do in New York?"
+      }
+    ]
+  }'
+```
+
+## License
+
+Trinity-Mini is released under the Apache-2.0 license.