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 license: apache-2.0
-base_model:
-- arcee-ai/Trinity-Nano-Preview
----
+base_model: arcee-ai/Trinity-Nano-Preview
+language:
+- en
+- es
+- fr
+- de
+- it
+- pt
+- ru
+- ar
+- hi
+- ko
+- zh
+---
+
+<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 Nano Preview
+
+Trinity Nano Preview is a preview of Arcee AI's 6B MoE model with 1B active parameters. It is the small-sized model in our new Trinity family, a series of open-weight models for enterprise and tinkerers alike.
+
+This is a chat tuned model, with a delightful personality and charm we think users will love. We note that this model is pushing the limits of sparsity in small language models with only 800M non-embedding parameters active per token, and as such **may be unstable** in certain use cases, especially in this preview.
+
+This is an *experimental* release, it's fun to talk to but will not be hosted anywhere, so download it and try it out yourself!
+
+***
+
+Trinity Nano Preview 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)
+
+***
+
+## Model Details
+
+* **Model Architecture:** AfmoeForCausalLM
+* **Parameters:** 6B, 1B 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)
+
+***
+
+<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
+
+- [Transformers](https://huggingface.co/arcee-ai/Trinity-Mini#transformers)
+- [VLLM](https://huggingface.co/arcee-ai/Trinity-Mini#vllm)
+- [llama.cpp](https://huggingface.co/arcee-ai/Trinity-Mini#llamacpp)
+- [LM Studio](https://huggingface.co/arcee-ai/Trinity-Mini#lm-studio)
+
+## Transformers.js
+
+Use the `v4` transformers preview version
+
+```
+npm i @huggingface/transformers@next
+```
+
+You can then run the model as follows:
+
+```js
+import { pipeline, TextStreamer } from "@huggingface/transformers";
+
+// Create a text generation pipeline
+const generator = await pipeline(
+  "text-generation",
+  "onnx-community/Trinity-Nano-Preview-ONNX",
+  { device: "webgpu", dtype: "q4f16" },
+);
+
+// Define the list of messages
+const messages = [
+  { role: "system", content: "You are a helpful assistant." },
+  { role: "user", content: "Write me a poem about Machine Learning." },
+];
+
+// Generate a response
+const output = await generator(messages, {
+  max_new_tokens: 512,
+  do_sample: false,
+  streamer: new TextStreamer(generator.tokenizer, { skip_prompt: true, skip_special_tokens: true }),
+});
+console.log(output[0].generated_text.at(-1).content);
+```
+
+## License
+
+Trinity-Nano-Preview is released under the Apache-2.0 license.