kdeng03/MolQwen3-4B-Instruct-SFT
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 16, 2026Architecture:Transformer Featherless Exclusive Cold
The kdeng03/MolQwen3-4B-Instruct-SFT is a 4 billion parameter instruction-tuned causal language model with a 32768 token context length. Developed by kdeng03, this model is designed for general-purpose conversational AI tasks. Its instruction-following capabilities make it suitable for a wide range of applications requiring natural language understanding and generation.
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Model Overview
The kdeng03/MolQwen3-4B-Instruct-SFT is an instruction-tuned causal language model featuring 4 billion parameters and a substantial context window of 32768 tokens. This model is developed by kdeng03 and is designed to understand and generate human-like text based on given instructions.
Key Capabilities
- Instruction Following: The model is fine-tuned to accurately interpret and respond to a variety of user instructions.
- Extended Context: With a 32768 token context length, it can process and generate longer, more coherent responses, maintaining context over extended conversations or documents.
- General-Purpose Language Generation: Capable of performing diverse natural language processing tasks, including question answering, summarization, and creative writing, based on its instruction-tuned nature.
Good For
- Conversational AI: Ideal for chatbots, virtual assistants, and interactive applications that require robust instruction-following.
- Content Generation: Suitable for generating various forms of text content, from creative stories to informative summaries.
- Research and Development: Provides a solid base for further fine-tuning on specific domain-specific tasks due to its general instruction-tuned capabilities.