Search Results for "pyscripter python 2"
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Showing 19 open source projects for "pyscripter python 2"
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Chinese-LLaMA-Alpaca 2
Chinese LLaMA-2 & Alpaca-2 Large Model Phase II Project
This project is developed based on the commercially available large model Llama-2 released by Meta. It is the second phase of the Chinese LLaMA&Alpaca large model project. The Chinese LLaMA-2 base model and the Alpaca-2 instruction fine-tuning large model are open-sourced. These models expand and optimize the Chinese vocabulary on the basis of the original Llama-2, use large-scale Chinese data for incremental pre-training, and further improve the basic semantics and command understanding... -
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Chinese-LLaMA-Alpaca-2 v2.0
Chinese LLaMA & Alpaca large language model + local CPU/GPU training
This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which... -
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Hunyuan3D 2.0
High-Resolution 3D Assets Generation with Large Scale Diffusion Models
The Hunyuan3D-2 model, developed by Tencent, is designed for generating high-resolution 3D assets using large-scale diffusion models. This model offers advanced capabilities for creating detailed 3D models, including texture enhancements, multi-view shape generation, and rapid inference for real-time applications. It is particularly useful for industries requiring high-quality 3D content, such as gaming, film, and virtual reality. Hunyuan3D-2 supports various enhancements and is available... -
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Stable Diffusion
High-Resolution Image Synthesis with Latent Diffusion Models
Stable Diffusion Version 2. The Stable Diffusion project, developed by Stability AI, is a cutting-edge image synthesis model that utilizes latent diffusion techniques for high-resolution image generation. It offers an advanced method of generating images based on text input, making it highly flexible for various creative applications. The repository contains pretrained models, various checkpoints, and tools to facilitate image generation tasks, such as fine-tuning and modifying the models... -
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GPT Neo
An implementation of model parallel GPT-2 and GPT-3-style models
... inefficient at those scales. This, as well as the fact that many GPUs became available to us, among other things, prompted us to move development over to GPT-NeoX. All evaluations were done using our evaluation harness. Some results for GPT-2 and GPT-3 are inconsistent with the values reported in the respective papers. We are currently looking into why, and would greatly appreciate feedback and further testing of our eval harness. -
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phi-2
Small, high-performing language model for QA, chat, and code tasks
Phi-2 is a 2.7 billion parameter Transformer model developed by Microsoft, designed for natural language processing and code generation tasks. It was trained on a filtered dataset of high-quality web content and synthetic NLP texts created by GPT-3.5, totaling 1.4 trillion tokens. Phi-2 excels in benchmarks for common sense, language understanding, and logical reasoning, outperforming most models under 13B parameters despite not being instruction-tuned or aligned via RLHF. It performs best... -
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Llama-2-7b
7B-parameter foundational LLM by Meta for text generation tasks
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 in English. It has 7 billion parameters and uses an optimized transformer-based, autoregressive architecture. Trained on 2 trillion tokens of publicly available data, it serves as the base for fine-tuned models like Llama-2-Chat. The model is pretrained only, meaning it is not optimized for dialogue but can be adapted for various natural language... -
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stable-diffusion-2-1
Latent diffusion model for high-quality text-to-image generation
Stable Diffusion 2.1 is a text-to-image generation model developed by Stability AI, building on the 768-v architecture with additional fine-tuning for improved safety and image quality. It uses a latent diffusion framework that operates in a compressed image space, enabling faster and more efficient image synthesis while preserving detail. The model is conditioned on text prompts via the OpenCLIP-ViT/H encoder and supports generation at resolutions up to 768×768. Released under the... -
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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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GPT-2
GPT-2 is a 124M parameter English language model for text generation
GPT-2 is a pretrained transformer-based language model developed by OpenAI for generating natural language text. Trained on 40GB of internet data from outbound Reddit links (excluding Wikipedia), it uses causal language modeling to predict the next token in a sequence. The model was trained without human labels and learns representations of English that support text generation, feature extraction, and fine-tuning. GPT-2 uses a byte-level BPE tokenizer with a vocabulary of 50,257 and handles... -
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Llama-2-7b-chat-hf
Dialogue-optimized 7B language model for safe and helpful chatting
Llama-2-7b-chat-hf is a fine-tuned large language model developed by Meta, designed specifically for dialogue use cases. With 7 billion parameters and built on an optimized transformer architecture, it uses supervised fine-tuning and reinforcement learning with human feedback (RLHF) to enhance helpfulness, coherence, and safety. It outperforms most open-source chat models and rivals proprietary systems like ChatGPT in human evaluations. Trained on 2 trillion tokens of public text and over 1... -
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Mistral-7B-Instruct-v0.2
Instruction-tuned 7B model for chat and task-oriented text generation
Mistral-7B-Instruct-v0.2 is a fine-tuned version of the Mistral-7B-v0.2 language model, designed specifically for following instructions in a conversational format. It supports a 32k token context window, enabling more detailed and longer interactions compared to its predecessor. The model is trained to respond to user prompts formatted with [INST] and [/INST] tags, and it performs well in instruction-following tasks like Q&A, summarization, and explanations. It can be used via the official... -
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Llama-2-70b-chat-hf
Llama-2-70B-Chat is Meta’s largest fine-tuned open-source chat LLM
Llama-2-70B-Chat is Meta’s largest fine-tuned large language model, optimized for dialogue and aligned using supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF). It features 70 billion parameters and uses a transformer architecture with grouped-query attention (GQA) to improve inference scalability. Trained on 2 trillion tokens from publicly available sources and over a million human-annotated examples, the model outperforms most open-source chat models and rivals... -
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stable-diffusion-xl-base-1.0
Advanced base model for high-quality text-to-image generation
stable-diffusion-xl-base-1.0 is a next-generation latent diffusion model developed by Stability AI for producing highly detailed images from text prompts. It forms the core of the SDXL pipeline and can be used on its own or paired with a refinement model for enhanced results. This base model utilizes two pretrained text encoders—OpenCLIP-ViT/G and CLIP-ViT/L—for richer text understanding and improved image quality. The model supports two-stage generation, where the base model creates initial... -
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Mistral 7B
A powerful, efficient language model designed for high-performance
Mistral 7B is a 7.3-billion-parameter language model that outperforms several competing models, including Llama 2 13B, across various benchmarks. Notably, it excels in tasks related to reasoning, comprehension, and code generation, while maintaining impressive performance on general English tasks. The model uses advanced techniques like Grouped-Query Attention (GQA) for faster inference and Sliding Window Attention (SWA) to efficiently handle longer sequences. Released under the Apache 2.0... -
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whisper-large-v3
High-accuracy multilingual speech recognition and translation model
... input and better support for Cantonese, achieving up to 20% error reduction over Whisper-large-v2. It handles zero-shot transcription and translation, performs language detection automatically, and supports features like word-level timestamps and long-form audio processing. The model integrates well with Hugging Face Transformers and supports optimizations such as batching, SDPA, and Flash Attention 2. -
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Meta-Llama-3-8B-Instruct
Instruction-tuned 8B LLM by Meta for helpful, safe English dialogue
... available data and more than 10 million human-annotated examples, it excludes any Meta user data. The model is released under the Meta Llama 3 Community License, which allows commercial use for organizations with fewer than 700 million MAUs, and imposes clear use, attribution, and redistribution rules. Meta provides safety tools like Llama Guard 2 and Code Shield to help developers implement system-level safety in applications. -
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whisper-large-v3-turbo
Whisper-large-v3-turbo delivers fast, multilingual speech recognition
..., temperature fallback, and timestamp prediction. Whisper-large-v3-turbo works with long-form and real-time audio, with chunked or sequential inference options. Optimizations such as torch.compile, Flash Attention 2, and SDPA are available to enhance performance. Despite being smaller than v3, it retains strong robustness to accents, noise, and zero-shot tasks, making it ideal for scalable, multilingual ASR use cases. -
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stable-diffusion-v1-4
Text-to-image diffusion model for high-quality image generation
stable-diffusion-v1-4 is a high-performance text-to-image latent diffusion model developed by CompVis. It generates photo-realistic images from natural language prompts using a pretrained CLIP ViT-L/14 text encoder and a UNet-based denoising architecture. This version builds on v1-2, fine-tuned over 225,000 steps at 512×512 resolution on the “laion-aesthetics v2 5+” dataset, with 10% text-conditioning dropout for improved classifier-free guidance. It is optimized for use with Hugging Face’s...
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