yuq-zhou/2026-05-o-b1p0-a1p0-gc0p5-exp-td4p0-tw10p0-mbz-r1-7-last
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 10, 2026Architecture:Transformer Featherless Exclusive Cold
The yuq-zhou/2026-05-o-b1p0-a1p0-gc0p5-exp-td4p0-tw10p0-mbz-r1-7-last is a 7.6 billion parameter causal language model with a 32,768 token context length. This model is presented as a research artifact backup in standard HuggingFace format. Its primary purpose is to serve as a checkpoint for ongoing research, making it suitable for developers exploring experimental model states.
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Model Overview
The yuq-zhou/2026-05-o-b1p0-a1p0-gc0p5-exp-td4p0-tw10p0-mbz-r1-7-last is a 7.6 billion parameter causal language model. It features a substantial context window of 32,768 tokens, allowing it to process and generate longer sequences of text.
Key Characteristics
- Parameter Count: 7.6 billion parameters.
- Context Length: Supports a context window of 32,768 tokens.
- Format: Provided in standard HuggingFace format, compatible with
AutoModelForCausalLM.from_pretrained. - Nature: Described as a research artifact backup, indicating its origin from an experimental or developmental phase.
Intended Use Cases
This model is primarily a research artifact. It is suitable for:
- Experimental Development: Researchers and developers interested in exploring specific checkpoints from an ongoing model development process.
- Replication Studies: Users looking to replicate or analyze the state of a model at a particular point in its training.
- Advanced Prototyping: For those who need a model with a large context window for experimental applications, understanding that it represents a specific, potentially non-final, development stage.