hjchoi47/Qwen3-0.6B-JSON-SFT
The hjchoi47/Qwen3-0.6B-JSON-SFT is a 0.8 billion parameter language model, likely based on the Qwen architecture, fine-tuned for specific tasks. This model is designed for use cases requiring a compact yet capable language model. Its primary differentiator and specific optimization target are not detailed in the provided information, suggesting it may be a base or general-purpose fine-tune.
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Model Overview
The hjchoi47/Qwen3-0.6B-JSON-SFT is a language model with approximately 0.8 billion parameters. The model card indicates it is a Hugging Face Transformers model, automatically generated, but lacks specific details regarding its development, funding, or precise model type. It is presented as a finetuned model, though the base model and finetuning specifics are not provided.
Key Characteristics
- Parameter Count: Approximately 0.8 billion parameters, making it a relatively compact model.
- Context Length: The model supports a context length of 32768 tokens.
- Origin: Shared by hjchoi47, likely derived from the Qwen model family.
Intended Use and Limitations
The model card does not specify direct or downstream use cases, nor does it detail out-of-scope uses. Information regarding biases, risks, and limitations is also marked as "More Information Needed." Users are advised to be aware of potential risks, biases, and limitations, as is standard for language models. Specific training data, procedures, hyperparameters, and evaluation results are not provided in the current model card.
Getting Started
While specific code examples are not included, the model is intended to be used with the Hugging Face Transformers library. Users would typically load it using AutoModelForCausalLM and AutoTokenizer.