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transformation

Recent Activity

sequelbox 
posted an update 4 days ago
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Multiple new releases for Gemma 4!

For Gemma 4 31B: Guardpoint, our medical reasoning model, trained on medical knowledge, management, diagnosis, and tasks:
- Structured medical reasoning responses are efficient and informative, cutting token costs for faster inference!
- Wide-ranging knowledge base: trained on a wide variety of medical disciplines, patient types, and query structures!
- High quality medical responses emphasize performance, brevity, specificity, statistical rationality, and openness.

Get Guardpoint for Gemma 4: ValiantLabs/gemma-4-31B-it-Guardpoint

For Gemma 4 E4B and E2B: Shining Valiant 3, our science-reasoning model!
- Science-reasoning: physics, biology, chemistry, compsci, astronomy, Earth science, and information theory.
- AI to build AI: high-quality reasoning performance on AI, MLOps, math and CUDA, complex adaptive and agentic systems, cognition, logic, linguistics, simulation, knowledge management, and more!
- Supplemented creative reasoning and general chat performance.

Get the new SV3 models:
E4B: ValiantLabs/gemma-4-E4B-it-ShiningValiant3
E2B: ValiantLabs/gemma-4-E2B-it-ShiningValiant3

We're working on several things - most excitingly, we've officially started the dataset curation process for Esper 4! We're focused on enhanced agentic capability and higher-dififculty, higher-value tasks this time, very excited to bring this to everyone when we can :)

Help support our releases, donations used for our experimental models and datasets: sequelbox/SupportOpenSource

Fight for open source with us!

for love and friendship,
allegra
sequelbox 
posted an update about 1 month ago
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Multiple new releases for Qwen 3.5 27B!

Firstly, Guardpoint, our medical reasoning model; trained on medical knowledge, management, diagnosis, and tasks:
- Structured medical reasoning responses are efficient and informative, cutting token costs for faster inference!
- Wide-ranging knowledge base: trained on a wide variety of medical disciplines, patient types, and query structures!
- High quality medical responses emphasize performance, brevity, specificity, statistical rationality, and openness.

Get Guardpoint for Qwen 3.5 27B: ValiantLabs/Qwen3.5-27B-Guardpoint

Secondly, we've also brought DAG Reasoning to Qwen 3.5 27B:
- Create structured, analytical Directed Acyclic Graphs to provide insight into your queries and situations!
- Multi-step analysis identifies causal relationships, produces confidence measurements, and forms a single structured graph object.
- DAG Reasoning Format provides clear, readable JSON containing structured, useful information; easy to use for creating visualizations, doing analysis, or further conversation with your assistant.
- Trained in a variety of subjects for flexible analysis: programming, science, business, economics, finance, law, logistics, management, and more!

Get the newest DAG Reasoning release: sequelbox/Qwen3.5-27B-DAG-Reasoning

We also have Esper 3.1 available for Qwen 3.5 27B - focused on high-performance coding, DevOps, and architecture: ValiantLabs/Qwen3.5-27B-Esper3.1

We'll have a lot more to come for the high-performance Qwen 3.5! Most of it is waiting for Deepseek V4 to come out first :) We've got some fun ideas!

Help support our releases, donations used for our experimental models and datasets: sequelbox/SupportOpenSource

Fight for open source with us! We've got a lot to do.

for friendship,
allegra
sequelbox 
posted an update about 2 months ago
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IMPORTANT corrective note/apology: the initial upload of ValiantLabs/Qwen3.5-27B-Esper3.1 contained improperly merged weights, meaning it was effectively just Qwen 3.5. We've merged properly now and re-uploaded the correct weights to the existing repository.

The model link is here: ValiantLabs/Qwen3.5-27B-Esper3.1

This is not at all the fault of Qwen 3.5, transformers, or anything other than our own flawed upload pipeline and insufficient post-upload validation. We have to do better. We'll immediately improve our validation procedures to be more rigorous. This will never happen again.

We are proud to build quickly: by providing a quick finetune of a new high-performance model like Qwen 3.5, we seek to provide value not only in the model's direct use but especially to our fellow open-source creators, who can learn from our initial training attempt. We are proud that building fast helps you build fast. In this case, our poor work has produced the opposite result - we've wasted your time. We are really sorry to everyone, but especially our fellow builders.

We feel about one inch tall right now, but we're going to get back to work and do better. Our crew deserves better and so do our users.

Humbly, your captain,
t.d.a.g.
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