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Open-weight model · Text classification
by Parallax Labs parallaxlabs/parallax-2-preview
parallax-2-preview is an open-weight model for text classification from Parallax Labs, released under Apache License 2.0. Its published files total 4.9 GB.
Parallax 2 Preview is the first public look at Parallax Labs' upcoming Parallax-2 model. It's a 4B finetune of Qwen 3.5, trained specifically to reason through problems carefully, like a frontier model would.
By Parallax Labs, published under apache-2.0, revision e1d8bbcf4600.
Parallax 2 Preview is the first public look at Parallax Labs' upcoming Parallax-2 model. It's a 4B finetune of Qwen 3.5, trained specifically to reason through problems carefully, like a frontier model would. Parallax-2-preview is a 4B parameter finetune designed to demonstrate structured reasoning at small scale. It uses the reasoning style of frontier models, while remaining fast enough to run on consumer hardware. Parallax 2 Preview is intended for reasoning-heavy tasks where a short, direct answer isn't the goal. Suitable for further finetuning into reasoning-focused applications, education tools, or as a component in multi-model pipelines where structured reasoning is the required…
Parallax 2 Preview is the first public look at Parallax Labs' upcoming Parallax-2 model. It's a 4B finetune of Qwen 3.5, trained specifically to reason through problems carefully, like a frontier model would.
Parallax-2-preview is a 4B parameter finetune designed to demonstrate structured reasoning at small scale. It uses the reasoning style of frontier models, while remaining fast enough to run on consumer hardware.
Parallax 2 Preview is intended for reasoning-heavy tasks where a short, direct answer isn't the goal.
Suitable for further finetuning into reasoning-focused applications, education tools, or as a component in multi-model pipelines where structured reasoning is the required output format.
Parallax 2 Preview is not intended for:
5 files, 4.9 GB in total. The weights are 2 files totalling 4.9 GB in gguf.
| File | Type | Size | SHA-256 |
|---|---|---|---|
| parallax-labs.parallax-2-preview.Q2_K_L.gguf | Weights | 2.1 GB | 373874cf5652 |
| parallax-labs.parallax-2-preview.Q4_K_M.gguf | Weights | 2.8 GB | 8545927e5ae7 |
| README.md | Documentation | 2.8 KB | — |
| 3ad25a2400279b7d7f22d488b6bf067c4d25cb81.png | Other | 1.6 KB | — |
| .gitattributes | Repository | 1.7 KB | — |
Released by Parallax Labs through its official repository on Hugging Face. Read the license.
| Precision | Weights in memory |
|---|---|
| As published | 4.9 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Yes. parallax-2-preview is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.
This is a RoBERTa-base model trained on ~124M tweets from January 2018 to December 2021, and finetuned for sentiment analysis with the TweetEval benchmark. The original Twitter-based RoBERTa model can be found here and the original reference paper is TweetEval. This model is suitable for English. 0 -> Negative; 1 -> Neutral; 2 -> Positive This sentiment analysis model has been integrated into TweetNLP. You can access the demo here.
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