Search Results for "text summarization java code"
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Showing 6 open source projects for "text summarization java code"
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Qwen
Qwen (通义千问) chat/pretrained large language model Alibaba Cloud
Qwen is a series of large language models developed by Alibaba Cloud, consisting of various pretrained versions like Qwen-1.8B, Qwen-7B, Qwen-14B, and Qwen-72B. These models, which range from smaller to larger configurations, are designed for a wide range of natural language processing tasks. They are openly available for research and commercial use, with Qwen's code and model weights shared on GitHub. Qwen's capabilities include text generation, comprehension, and conversation, making... -
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BLEURT-20-D12
Custom BLEURT model for evaluating text similarity using PyTorch
BLEURT-20-D12 is a PyTorch implementation of BLEURT, a model designed to assess the semantic similarity between two text sequences. It serves as an automatic evaluation metric for natural language generation tasks like summarization and translation. The model predicts a score indicating how similar a candidate sentence is to a reference sentence, with higher scores indicating greater semantic overlap. Unlike standard BLEURT models from TensorFlow, this version is built from a custom PyTorch... -
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gemma-7b
Compact, state-of-the-art LLM by Google for text generation tasks
Gemma-7B is a lightweight, open-source, decoder-only language model developed by Google, built using the same research and technology behind the Gemini family. With 8.5 billion parameters and an 8192-token context window, it is optimized for English text generation tasks like question answering, summarization, reasoning, and creative writing. Trained on 6 trillion tokens including web documents, code, and mathematical texts, Gemma-7B provides competitive performance across a wide range of NLP... -
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Llama-3.2-1B-Instruct
Instruction-tuned 1.2B LLM for multilingual text generation by Meta
Llama-3.2-1B-Instruct is Meta’s multilingual, instruction-tuned large language model with 1.24 billion parameters, optimized for dialogue, summarization, and retrieval tasks. It builds upon the Llama 3.1 architecture and incorporates fine-tuning techniques like SFT, DPO, and quantization-aware training for improved alignment, efficiency, and safety. The model supports eight primary languages (including English, Spanish, Hindi, and Thai) and was trained on a curated mix of publicly available... -
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Llama-2-7b-hf
Llama-2-7B is a 7B-parameter transformer model for text generation
Llama-2-7B is a foundational large language model developed by Meta as part of the Llama 2 family, designed for general-purpose text generation tasks. It is a 7 billion parameter auto-regressive transformer trained on 2 trillion tokens from publicly available sources, using an optimized architecture without Grouped-Query Attention (GQA). This model is the pretrained version, intended for research and commercial use in English, and can be adapted for downstream applications such as summarization... -
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Llama-2-7b
7B-parameter foundational LLM by Meta for text generation tasks
... processing tasks, such as summarization, completion, and code generation. It demonstrates solid performance on academic benchmarks like MMLU and TruthfulQA, improving on its predecessor, Llama 1. The Llama-2-7B model is released under Meta’s Llama 2 Community License, which allows for commercial use under certain conditions, especially for companies with fewer than 700 million MAUs.
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