yuq-zhou/2026-05-o-b0p3-a1p0-gc0p33-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 12, 2026Architecture:Transformer Featherless Exclusive Cold
The yuq-zhou/2026-05-o-b0p3-a1p0-gc0p33-exp-td4p0-tw10p0-mbz-r1-7-last model is a 7.6 billion parameter causal language model developed by yuq-zhou. This model is a research artifact backup, provided in standard HuggingFace format for `AutoModelForCausalLM.from_pretrained`. With a context length of 32768 tokens, it is suitable for general language generation and understanding tasks.
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Model Overview
The yuq-zhou/2026-05-o-b0p3-a1p0-gc0p33-exp-td4p0-tw10p0-mbz-r1-7-last is a 7.6 billion parameter causal language model. It is provided as a research artifact backup in the standard HuggingFace format, making it directly compatible with AutoModelForCausalLM.from_pretrained for easy integration into existing workflows.
Key Characteristics
- Parameter Count: 7.6 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a substantial context window of 32768 tokens, enabling the processing of longer inputs and generating more coherent, extended outputs.
- Format: Distributed in the standard HuggingFace format, ensuring broad compatibility and ease of use within the HuggingFace ecosystem.
Good For
- Research and Development: Ideal for researchers and developers exploring large language models, particularly those interested in the specific configuration and training represented by this artifact.
- General Language Tasks: Suitable for a wide range of natural language processing applications, including text generation, summarization, and question answering, given its causal language modeling architecture and significant parameter count.