Search Results for "python programming language" - Page 25
Sort By:
Showing 630 open source projects for "python programming language"
View related business solutions-
Gen AI apps are built with MongoDB AtlasMongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
webXcreta users natural language processing to create grammatical averages of textual communication and then generate original content based on these statistics.
-
2
Solve Logic Word Puzzles with CLP
Constraint Logic can solve word logic puzzles.
Learn basic constraint logic programming by solving logic word puzzles. Go to http://eclipse.dougedmunds.com . This tutorial will show you how to solve easy 1 star to hard 5 star puzzles, using the eCLiPSe-CLP language (available at http://eclipseclp.org/). Don't confuse this programming language (a prolog language) with the IDE for Java. -
3
NewsNotFound
This is the entire source code for NewsNotFound's article gen process
Our mission is to lead the way in AI journalism by providing completely neutral and unbiased news articles that can be governed by the public. NewsNotFound is a news website located at https://newsnotfound.com. We want to build the most unbiased news platform on the internet. -
4
bloom
Multilingual 176B language model for text and code generation tasks
BLOOM (BigScience Large Open-science Open-access Multilingual Language Model) is a 176-billion parameter autoregressive language model developed by the BigScience Workshop. It generates coherent text in 46 natural languages and 13 programming languages, making it one of the most multilingual LLMs publicly available. BLOOM was trained on 366 billion tokens using Megatron-DeepSpeed and large-scale computational resources. It can perform various tasks via prompt-based learning, even without task... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
5
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... -
6
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... -
7
Some NLP experiments starting with a tokenization attempt in Python. The code tokenite.py reads a text file "blog1.txt" and tries to tokenize it. The code doesnot work as is, but is almost on the verge of working. Any suggestions will be greatly appreciated. I define a class called text and define methods inside it. The method count defines a generator which I use in the method named t_tok. But if you look closely at 66 to 72 you will see that I am modifying the outer limit of the for loop...
-
8
OpenVLA 7B
Vision-language-action model for robot control via images and text
OpenVLA 7B is a multimodal vision-language-action model trained on 970,000 robot manipulation episodes from the Open X-Embodiment dataset. It takes camera images and natural language instructions as input and outputs normalized 7-DoF robot actions, enabling control of multiple robot types across various domains. Built on top of LLaMA-2 and DINOv2/SigLIP visual backbones, it allows both zero-shot inference for known robot setups and parameter-efficient fine-tuning for new domains. The model... -
9
DeepSeek-R1-0528
DeepSeek-R1-0528 is a powerful reasoning-focused LLM with 64K context
DeepSeek-R1-0528 is an upgraded large language model developed by DeepSeek AI, designed to improve deep reasoning, inference, and programming capabilities. With a context length of up to 64K tokens and 685 billion parameters, it introduces enhanced algorithmic optimizations and expanded token usage per task. Compared to previous versions, it significantly improves benchmark scores in math (e.g., AIME 2025: 87.5%), logic, and coding tasks like LiveCodeBench and SWE Verified. It supports system... -
Turn Your Content into Interactive Magic - For FreeTransform anything you share into an engaging digital experience - for free. Instantly convert your PDFs, slides, and files into dynamic, interactive sessions with built-in collaboration tools, activities, and real-time assessment. From teaching to training to team building, make every presentation unforgettable. Used by millions for education, business, and professional development.
-
10
ERNIE-4.5-300B-A47B-FP8-Paddle
ERNIE 4.5 MoE model in FP8 for efficient high-performance inference
ERNIE-4.5-300B-A47B-FP8-Paddle is a quantized version of Baidu’s MoE large language model, post-trained for text generation tasks and optimized for FP8 precision. This variant retains the original’s 300 billion total parameters with 47 billion active per token, enabling powerful language understanding while dramatically improving inference efficiency. Built using PaddlePaddle, it supports multi-GPU distributed deployment and leverages advanced routing strategies and expert parallelism... -
11
Devstral
Agentic 24B LLM optimized for coding tasks with 128k context support
..., compatible with frameworks like vLLM, Transformers, llama.cpp, and Ollama. It is licensed under Apache 2.0 and is fully open for commercial and non-commercial use. Its Tekken tokenizer allows a 131k vocabulary size for high flexibility in programming languages and natural language inputs. Devstral is the preferred backend for OpenHands, where it acts as the reasoning engine for autonomous code agents. -
12
DeepSeek-V3-0324
Advanced multilingual LLM with enhanced reasoning and code generation
DeepSeek-V3-0324 is a powerful large language model by DeepSeek AI that significantly enhances performance over its predecessor, especially in reasoning, programming, and Chinese language tasks. It achieves major benchmark improvements, such as +5.3 on MMLU-Pro and +19.8 on AIME, and delivers more executable, aesthetically improved front-end code. Its Chinese writing and search-answering capabilities have also been refined, generating more fluent, contextually aware long-form outputs. Key... -
13
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... -
14
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... -
15
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... -
16
chatglm-6b
Bilingual 6.2B parameter chatbot optimized for Chinese and English
ChatGLM-6B is a 6.2 billion parameter bilingual language model developed by THUDM, based on the General Language Model (GLM) framework. It is optimized for natural and fluent dialogue in both Chinese and English, supporting applications in conversational AI, question answering, and assistance. Trained on approximately 1 trillion tokens, the model benefits from supervised fine-tuning, feedback self-training, and reinforcement learning with human feedback to align its outputs with human... -
17
ERNIE-4.5-0.3B-Base-PT
Compact 360M text model with high efficiency and fine-tuning support
ERNIE-4.5-0.3B-Base-PT is a compact, fully dense transformer model with 360 million parameters, optimized for general-purpose text generation tasks. It belongs to the ERNIE 4.5 series by Baidu and leverages advanced pretraining techniques without relying on a Mixture-of-Experts (MoE) structure. The model features 18 transformer layers, 16 attention heads, and a maximum context length of 131,072 tokens, offering strong language understanding for its size. It can be fine-tuned using ERNIEKit... -
18
Nanonets-OCR-s
State-of-the-art image-to-markdown OCR model
Nanonets-OCR-s is an advanced image-to-markdown OCR model that transforms documents into structured and semantically rich markdown. It goes beyond basic text extraction by intelligently recognizing content types and applying meaningful tags, making the output ideal for Large Language Models (LLMs) and automated workflows. The model expertly converts mathematical equations into LaTeX syntax, distinguishing between inline and display modes for accuracy. It also generates descriptive <img> tags... -
19
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. -
20
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 (RLHF... -
21
Meta-Llama-3-8B-Instruct
Instruction-tuned 8B LLM by Meta for helpful, safe English dialogue
Meta-Llama-3-8B-Instruct is an instruction-tuned large language model from Meta’s Llama 3 family, optimized for safe and helpful English dialogue. It uses an autoregressive transformer architecture with Grouped-Query Attention (GQA) and supports an 8k token context length. Fine-tuned using supervised learning and reinforcement learning with human feedback (RLHF), the model achieves strong results on benchmarks like MMLU, GSM8K, and HumanEval. Trained on over 15 trillion tokens of publicly... -
22
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... -
23
ⓍTTS-v2
Multilingual voice cloning TTS model with 6-second sample support
ⓍTTS-v2 (XTTS-v2) by Coqui is a powerful multilingual text-to-speech model capable of cloning voices from a short 6-second audio sample. It supports 17 languages and enables high-quality voice generation with emotion, style transfer, and cross-language synthesis. The model introduces major improvements over ⓍTTS-v1, including better prosody, stability, and support for Hungarian and Korean. ⓍTTS-v2 allows interpolation between multiple voice references and generates speech at a 24kHz sampling... -
24
whisper-large-v3-turbo
Whisper-large-v3-turbo delivers fast, multilingual speech recognition
Whisper-large-v3-turbo is a high-performance automatic speech recognition (ASR) and translation model developed by OpenAI, based on a pruned version of Whisper large-v3. It reduces decoding layers from 32 to 4, offering significantly faster inference with only minor degradation in accuracy. Trained on over 5 million hours of multilingual data, it handles speech transcription, translation, and language identification across 99 languages. It supports advanced decoding strategies like beam search... -
25
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...
