dhf1234/OpsLM-v1
TEXT GENERATIONConcurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 22, 2026Architecture:Transformer Featherless Exclusive Cold
OpsLM-v1 by dhf1234 is a 4 billion parameter language model, finetuned and converted to GGUF format using Unsloth. This model is based on the Qwen3-4b-base architecture and is optimized for efficient deployment and inference. Its primary differentiator is the use of Unsloth for accelerated training and GGUF conversion, making it suitable for local inference on various hardware.
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OpsLM-v1 Overview
OpsLM-v1 is a 4 billion parameter language model developed by dhf1234, specifically finetuned and converted into the GGUF format. This model leverages the qwen3-4b-base architecture, indicating its foundation in the Qwen series of models.
Key Characteristics
- Efficient Training: The model was trained using Unsloth, which facilitated a 2x faster training process compared to standard methods.
- GGUF Format: Provided in the GGUF format, making it highly compatible with
llama.cppand similar inference engines for efficient local deployment. - Parameter Count: With 4 billion parameters, it offers a balance between performance and computational requirements.
- Context Length: Supports a context length of 32768 tokens, allowing for processing of substantial input sequences.
Use Cases
OpsLM-v1 is particularly well-suited for:
- Local Inference: Its GGUF format and efficient training make it ideal for running on consumer-grade hardware.
- Applications requiring Qwen3-4b-base capabilities: Users familiar with the base model's strengths can expect similar performance characteristics.
- Developers seeking optimized models: The Unsloth integration highlights its suitability for projects prioritizing faster training and deployment workflows.