Tag

DS2API

Converts DeepSeek protocol calls into OpenAI/Claude/Gemini-compatible APIs with a Go backend and React admin UI. Offers account pooling, protocol adapters, tool-call translation, PoW, and multiple deployment modes (Docker, Vercel, standalone).

Nemotron-SFT-Math-v3

Large-scale mathematical reasoning dataset of model-generated solution trajectories produced with and without Python Tool-Integrated Reasoning (TIR), with final answers verified against reference solutions. Contains ~3.64M JSONL training samples (~144 GB) and per-source CC-BY / CC-BY-SA licensing; intended for training and evaluating tool-augmented mathematical reasoning in LLMs.

BugHunter

Terminal-first toolkit that automates bug bounty workflows — recon, hunting across 20 vulnerability classes, validation, and submission-ready report generation; runs as a Claude Code plugin or standalone CLI with support for free local AI providers (Ollama, Groq, DeepSeek).

dot-skill (colleague.skill)

Turns heterogeneous traces (chats, docs, emails, transcripts) into versioned, inspectable agent 'Skills' that capture both Persona and Work behaviors; supports multi-source collection, incremental merges and corrections, and installation across multiple agent hosts.

Reasonix (DeepSeek-Reasonix)

Terminal-native AI coding agent that runs as a single static Go binary and preserves long LLM sessions using DeepSeek-aware prefix caching. Config- and plugin-driven: supports multiple providers, separate planner/executor sessions, and CLI/TUI, desktop and VS Code integrations.

DeepSeek-V4-Flash

A 284B-parameter Mixture-of-Experts LLM with only 13B activated parameters, designed for 1,000,000-token contexts. Uses hybrid compressed attention and mixed FP4/FP8 precision to reduce long-context KV-cache and per-token FLOPs; aimed at long-document QA, RAG pipelines, and local/high-capacity inference.

DeepSeek-V4-Pro

Generates conversational and reasoning outputs with support for million‑token contexts; uses a hybrid attention + MoE design to cut long‑context inference FLOPs and KV cache. Suited for long‑document retrieval, coding and complex reasoning; MIT licensed.

DeepSeek-V4-Flash-Base

A vision-oriented foundation checkpoint for low-latency inference — DeepSeek V4 base in safetensors with FP8 optimizations. Designed for fast image generation and embedding use in inference pipelines; verify license and FP8/runtime compatibility before production use.

DeepSeek-V4-Pro-Base

Base image-generation foundation model tuned for visual search and prompt-guided synthesis, intended as a compact starting point for local inference or fine-tuning. Emphasizes easy integration into image pipelines and suitability for downstream adaptation.

DeepSeek-V4-Distill-8100x

Supervised fine-tuning dataset of 7,716 reasoning-focused Q&A examples distilled from the DeepSeek‑V4‑Flash teacher; provided as a cleaned JSONL train split for distillation and SFT experiments.

Deepseek-v4-pro-max-distill-1000x

1,000 JSONL samples containing full chain-of-thought reasoning traces and final answers produced by DeepSeek‑V4‑Pro for use in student-model distillation and quality checks. Prompts sampled from Jackrong/GLM-5.1-Reasoning-1M-Cleaned; Apache‑2.0 licensed.

beyoru/Deepseek-v4-pro-max-distill-1500x

Contains full chain-of-thought traces and final answers generated by DeepSeek-V4-Pro for use as distillation supervision. Key features: full CoT exposure, ~1,000 mixed-domain samples (JSONL/Parquet), Apache-2.0 license — suitable for training student models but watch for source contamination.