IdeaLens-NoParaphrase

IdeaLens detects who came up with the ideas in a document, rather than who wrote its words. It reads a role-labelled outline of the document (an ordered list of items, each giving one idea and the discourse role it plays, such as Central Development or Open Question) and returns P(human), the probability that the ideas are human. IdeaLens is nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16 fine-tuned with LoRA (rank 64) on the outlines of 1M English web documents (WildOutlines). The training outlines were paraphrased to remove the documents' wording, so the model has to fit its labels through the ideas. Try it in your browser: the IdeaLens & ProseLens demo scores your own text with both…

ProseLens detects who wrote the words of a document. It is IdeaLens's counterpart in the paper: the same backbone, training documents and labels, but it reads the raw document text instead of an outline, so it learns word-level provenance. It returns P(human), the probability that the document was written by a person. ProseLens is nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16 fine-tuned with LoRA (rank 64) on 1M English web documents (WildOutlines). Try it in your browser: the IdeaLens & ProseLens demo scores your own text with both detectors, no installation or keys needed. From the paper: ProseLens is accurate when a document's ideas and words come from the same source (99.1%), but…

Model · Text generation

Qwen2.5-32B-Instruct

Qwen

Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models in these domains. - Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON. More resilient to the diversity of system prompts, enhancing role-play implementation and…

Model · Text generation

Qwen2.5-32B-Instruct-AWQ

Qwen

Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models in these domains. - Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON. More resilient to the diversity of system prompts, enhancing role-play implementation and…

Model · Text generation

Qwen2.5-Coder-32B-Instruct-AWQ

Qwen

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). As of now, Qwen2.5-Coder has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters, to meet the needs of different developers. Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in code generation, code reasoning and code fixing. Base on the strong Qwen2.5, we scale up the training tokens into 5.5 trillion including source code, text-code grounding, Synthetic data, etc. Qwen2.5-Coder-32B has become the current state-of-the-art open-source codeLLM, with its coding abilities matching those of GPT-4o. - A more…

Model · Text generation

Qwen2.5-Coder-32B-Instruct

Qwen

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). As of now, Qwen2.5-Coder has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters, to meet the needs of different developers. Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in code generation, code reasoning and code fixing. Base on the strong Qwen2.5, we scale up the training tokens into 5.5 trillion including source code, text-code grounding, Synthetic data, etc. Qwen2.5-Coder-32B has become the current state-of-the-art open-source codeLLM, with its coding abilities matching those of GPT-4o. - A more…