Search Results for "chat application in python"
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Showing 17 open source projects for "chat application in python"
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gpt-oss
gpt-oss-120b and gpt-oss-20b are two open-weight language models
... for efficient memory use and support OpenAI’s Harmony response format, enabling transparent full chain-of-thought reasoning and advanced tool integrations such as function calling, browsing, and Python code execution. The repository provides multiple reference implementations—including PyTorch, Triton, and Metal—for educational and experimental use, as well as example clients and tools like a terminal chat app and a Responses API server. -
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Qwen3-Coder
Code version of Qwen3, the large language model by Alibaba Cloud
Qwen3-Coder is the latest and most powerful agentic code model developed by the Qwen team at Alibaba Cloud. Its flagship version, Qwen3-Coder-480B-A35B-Instruct, features a massive 480 billion-parameter Mixture-of-Experts architecture with 35 billion active parameters, delivering top-tier performance on coding and agentic tasks. This model sets new state-of-the-art benchmarks among open models for agentic coding, browser-use, and tool-use, matching performance comparable to leading models... -
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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 it a... -
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GLM-4-32B-0414
Open Multilingual Multimodal Chat LMs
GLM-4-32B-0414 is a powerful open-source large language model featuring 32 billion parameters, designed to deliver performance comparable to leading models like OpenAI’s GPT series. It supports multilingual and multimodal chat capabilities with an extensive 32K token context length, making it ideal for dialogue, reasoning, and complex task completion. The model is pre-trained on 15 trillion tokens of high-quality data, including substantial synthetic reasoning datasets, and further enhanced... -
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ChatGLM2-6B
An Open Bilingual Chat LLM | Open Source Bilingual Conversation LLM
ChatGLM2-6B is an advanced open-source bilingual dialogue model developed by THUDM. It is the second iteration of the ChatGLM series, designed to offer enhanced performance while maintaining the strengths of its predecessor, including smooth conversation flow and low deployment barriers. The model is fine-tuned for both Chinese and English languages, making it a versatile tool for various multilingual applications. ChatGLM2-6B aims to push the boundaries of natural language understanding and... -
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Warlock-Studio
Open-source AI suite for Windows with Real-ESRGAN, GFPGAN & RIFE. v4.1
Warlock-Studio is a powerful, open-source desktop application for Windows that integrates state-of-the-art AI models for video and image enhancement. This suite provides a unified, high-performance interface for upscaling, restoration, and frame interpolation, making advanced enhancement workflows accessible and efficient. Version 4.1 builds on previous improvements with enhanced GPU utilization, comprehensive compatibility fixes, and optimization of model loading processes to provide... -
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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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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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Dark GPT Free
Free chat GPT app without censorship!
This is the same GPT chat, but there are no restrictions and you can ask whatever you want. ATTENTION, Chrome blocks downloading .zip files, so to download our application you need to open the download page in Microsoft Edge or another browser except Chrome. Good luck! -
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ERNIE-4.5-VL-28B-A3B-Paddle
Multimodal ERNIE 4.5 MoE model for image-text reasoning and chat
ERNIE-4.5-VL-28B-A3B-Paddle is a multimodal MoE chat model designed for complex image-text tasks, featuring 28 billion total parameters with 3 billion activated per token. Built on PaddlePaddle, it excels in tasks like visual question answering, description generation, and multimodal reasoning. It employs a heterogeneous Mixture-of-Experts architecture that supports both thinking and non-thinking inference modes. The model benefits from advanced pretraining and posttraining strategies... -
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phi-2
Small, high-performing language model for QA, chat, and code tasks
... on QA-style prompts, code generation, and chat dialogues using structured input formats. The model has a context length of 2048 tokens and was trained over 14 days on 96 A100 GPUs using DeepSpeed and FlashAttention. Though compact, it still exhibits verbosity, potential bias, and may generate inaccurate or verbose code without supervision. Phi-2 is released under the MIT license to support open research on safe, controllable language modeling. -
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Mistral-7B-Instruct-v0.2
Instruction-tuned 7B model for chat and task-oriented text generation
... mistral_common tokenizer or Hugging Face’s transformers library, and supports generation on GPUs with BF16 precision. Built on a transformer architecture without sliding-window attention, the model is optimized for fast inference and chat integration. Though it lacks moderation mechanisms, it showcases the capability of Mistral-7B as a base for further fine-tuning and safety tooling. Mistral-7B-Instruct-v0.2 is licensed under Apache 2.0 and widely used across open-source projects. -
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Llama-3.1-8B-Instruct
Multilingual 8B-parameter chat-optimized LLM fine-tuned by Meta
Llama-3.1-8B-Instruct is a multilingual, instruction-tuned language model developed by Meta, designed for high-quality dialogue generation across eight languages, including English, Spanish, French, German, Italian, Portuguese, Hindi, and Thai. It uses a transformer-based, autoregressive architecture with Grouped-Query Attention and supports a 128k token context window. The model was fine-tuned using a combination of supervised fine-tuning (SFT), reinforcement learning with human feedback... -
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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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Llama-3.3-70B-Instruct
Llama-3.3-70B-Instruct is a multilingual AI optimized for helpful chat
Llama-3.3-70B-Instruct is Meta's large, instruction-tuned language model designed for safe, multilingual, assistant-style conversations and text generation. With 70 billion parameters, it supports English, Spanish, French, German, Italian, Portuguese, Hindi, and Thai, offering state-of-the-art performance across a wide range of benchmarks including MMLU, HumanEval, and GPQA. The model is built on a transformer architecture with grouped-query attention, trained on over 15 trillion tokens and... -
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Llama-2-7b-hf
Llama-2-7B is a 7B-parameter transformer model for text generation
..., question answering, and code generation. Llama-2-7B outputs text only, with input also restricted to text. Fine-tuned variants of this model, such as Llama-2-Chat, demonstrate competitive performance in dialogue tasks and safety benchmarks, rivaling proprietary models. The model was trained using Meta’s infrastructure, including 184,320 GPU hours and emissions fully offset by Meta’s sustainability program. -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
... for very long sequences. Trained using large-scale reinforcement learning on diverse tasks, it excels in mathematics, software engineering, agentic tool use, and long-context understanding benchmarks. It outperforms other open-weight models like DeepSeek R1 and Qwen3-235B on complex reasoning and coding challenges. MiniMax-M1 is available in two versions with 40K and 80K token thinking budgets, offering scalable performance based on your application needs.
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