Trinity-Mini-Base-Pre-Anneal 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 base model is a pre-anneal checkpoint captured at Adam LR: 0.002, Muon LR: 0.001 before starting learning rate decay on a high-quality data mix.
While this checkpoint was not exposed to the anneal phase mix containing high proportions of math and code content, it has been trained on significant amounts of such data.
This checkpoint is not suitable for chatting or general use without further finetuning and should be trained for your specific domain before use.
Trinity-Mini-Base-Pre-Anneal is trained on 8.8T tokens gathered and curated through a key partnership with
Datology
, building upon the excellent dataset we used on
AFM-4.5B
with additional math and code.
Training was performed on a cluster of 512 H200 GPUs powered by
Prime Intellect
using HSDP parallelism.
More details, including key architecture decisions, can be found on our blog
here
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-Base-Pre-Anneal is released under the Apache-2.0 license.
Runs of arcee-ai Trinity-Mini-Base-Pre-Anneal on huggingface.co
258
Total runs
0
24-hour runs
17
3-day runs
23
7-day runs
23
30-day runs
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Trinity-Mini-Base-Pre-Anneal is an open source model from GitHub that offers a free installation service, and any user can find Trinity-Mini-Base-Pre-Anneal on GitHub to install. At the same time, huggingface.co provides the effect of Trinity-Mini-Base-Pre-Anneal install, users can directly use Trinity-Mini-Base-Pre-Anneal installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
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