Search Results for "math language" - Page 5
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Showing 120 open source projects for "math language"
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Procbyte - Binary Scripting Language
Script language for processing binary data
Procbyte is a tool to access binary files from shell programming. It has binary data handling, read/write capability, basic math and date conversions. It is intended to aid in bash programming, but can be used from any command line tool or application. NOTE: This was accidentally uploaded as a beta, instead of alpha, but its status IS ALPHA. The next upload will standardize the language to the point where any scripts that work in it will work in all future versions -- however, scripts written for this version may not work in subsequent ones, the (mostly output) commands have changed: , ; . =* etc. ... -
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MathUtils is a small collection of usesful math-processing programs for Windows/Unix fammily, write in object pascal language. Applications are very simple to use.
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TekMath is a java/swing-based viewer for the Math Markup Language (MathML) that can be easily embedded in custom java applications. It supports both content and presentation markup languages, and depends on no external packages beyond the java runtime.
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FrAid(FRactal AID) is an interface to Java, allowing it to proc. math. data(functions/equations). A compl. standalone system utilizing the FrAid prog. lang. is available(no need to be Java programmer to use it!). Use instead of Matlab. High res. graphics
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TclTexEd is a great LaTex-Editor written in Tcl/Tk. It includes syntax highlighting, auto-completion and a multi language online help (english, german, indonesia and brazilian). Insert math symbols by simply clicking on Imagebuttons.
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MAED is a simple but powerfull math program with educational character. It has a Lisp like programming language, a nice GUI. It can work in client-server mode. A main goal is to make a program which can solve math problems using both numerical and symb
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Symbolic math Java applet. Features: big number arithmetic; symbolic and numeric evaluation; programming language constructs;plot functions
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STack Oriented Interactive Compiler Adapted to Linux. POSIX threads, regular expressions, sockets, associative arrays (hashes), dynamic memory/GC, floating point math, types, and more. An RPN language, inspired by STOIC and Forth.
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Are you a fan of FORTH/RPN math? Need an easy, quick way to access files, do calculations, or just about anything else on your computer? Enter CUE (abrv. Q). Optimized for short, quick programs this language can be used for many different chores.
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Ministral 3 8B Reasoning 2512
Efficient 8B multimodal model tuned for advanced reasoning tasks.
Ministral 3 8B Reasoning 2512 is a balanced midsize model in the Ministral 3 family, delivering strong multimodal reasoning capabilities within an efficient footprint. It combines an 8.4B-parameter language model with a 0.4B vision encoder, enabling it to process both text and images for advanced reasoning tasks. This version is specifically post-trained for reasoning, making it well-suited for math, coding, and STEM applications requiring multi-step logic and problem-solving. Despite its reasoning-focused training, the model remains edge-optimized and can run locally on a single 24GB GPU in BF16, or under 12GB when quantized. ... -
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Ministral 3 14B Reasoning 2512
High-precision 14B multimodal model built for advanced reasoning tasks
Ministral 3 14B Reasoning 2512 is the largest model in the Ministral 3 series, delivering frontier-level performance with capabilities comparable to the Mistral Small 3.2 24B model. It pairs a 13.5B-parameter language model with a 0.4B vision encoder, enabling strong multimodal reasoning across both text and images. This version is specifically post-trained for reasoning tasks, making it highly effective for math, coding, STEM workloads, and complex multi-step problem-solving. Despite its scale, the model is engineered for practical deployment and can run locally on 32GB of VRAM in BF16 or under 24GB when quantized. ... -
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Ministral 3 3B Reasoning 2512
Compact 3B-param multimodal model for efficient on-device reasoning
Ministral 3 3B Reasoning 2512 is the smallest reasoning-capable model in the Ministal-3 family, yet delivers a surprisingly capable multimodal and multilingual base for lightweight AI applications. It pairs a 3.4B-parameter language model with a 0.4B-parameter vision encoder, enabling it to understand both text and image inputs. This reasoning-tuned variant is optimized for tasks like math, coding, and other STEM-related problem solving, making it suitable for applications that require logical reasoning, analysis, or structured thinking. Despite its modest size, the model is designed for edge deployment and can run locally, fitting in ~16 GB of VRAM in BF16 or under 8 GB of RAM/VRAM when quantized. ... -
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QwQ-32B
QwQ-32B is a reasoning-focused language model for complex tasks
...The model is capable of structured thinking and delivers competitive performance against top models like DeepSeek-R1 and o1-mini. Recommended usage involves prompts starting with <think>\n, non-greedy sampling strategies, and support for standardized outputs on math and multiple-choice tasks. For long input handling, it supports YaRN (Yet another RoPE Namer) for context scaling. -
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Qwen2-7B-Instruct
Instruction-tuned 7B language model for chat and complex tasks
Qwen2-7B-Instruct is a 7.62-billion-parameter instruction-tuned language model from the Qwen2 series developed by Alibaba's Qwen team. Built on a transformer architecture with SwiGLU activation and group query attention, it is optimized for chat, reasoning, coding, multilingual tasks, and extended context understanding up to 131,072 tokens. The model was pretrained on a large-scale dataset and aligned via supervised fine-tuning and direct preference optimization. It shows strong performance... -
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ZAYA1-8B
Efficient MoE reasoning model for coding and math workloads
ZAYA1-8B is a compact Mixture-of-Experts reasoning model developed by Zyphra, designed to deliver unusually high intelligence density with fewer than 1 billion active parameters. The model contains 8.4B total parameters with around 760M active during inference, allowing it to achieve strong reasoning, mathematics, and coding performance while remaining lightweight enough for efficient local or on-device deployment. ZAYA1-8B is optimized for long-form reasoning and test-time compute... -
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VaultGemma
VaultGemma: 1B DP-trained Gemma variant for private NLP tasks
VaultGemma is a sub-1B parameter variant of Google’s Gemma family that is pre-trained from scratch with Differential Privacy (DP), providing mathematically backed guarantees that its outputs do not reveal information about any single training example. Using DP-SGD with a privacy budget across a large English-language corpus (web documents, code, mathematics), it prioritizes privacy over raw utility. The model follows a Gemma-2–style architecture, outputs text from up to 1,024 input tokens,... -
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Hermes 4
Hermes 4 FP8: hybrid reasoning Llama-3.1-405B model by Nous Research
Hermes 4 405B FP8 is a cutting-edge large language model developed by Nous Research, built on Llama-3.1-405B and optimized for frontier reasoning and alignment. It introduces a hybrid reasoning mode with explicit <think> segments, enabling the model to deliberate deeply when needed and switch to faster responses when desired. Post-training improvements include a vastly expanded corpus with ~60B tokens, boosting performance across math, code, STEM, logic, creativity, and structured outputs. ... -
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Qwen2.5-14B-Instruct
Powerful 14B LLM with strong instruction and long-text handling
Qwen2.5-14B-Instruct is a powerful instruction-tuned language model developed by the Qwen team, based on the Qwen2.5 architecture. It features 14.7 billion parameters and is optimized for tasks like dialogue, long-form generation, and structured output. The model supports context lengths up to 128K tokens and can generate up to 8K tokens, making it suitable for long-context applications. It demonstrates improved performance in coding, mathematics, and multilingual understanding across over...
