Showing 10 open source projects for "linux server"

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  • 1
    gpt-oss

    gpt-oss

    gpt-oss-120b and gpt-oss-20b are two open-weight language models

    gpt-oss is OpenAI’s open-weight family of large language models designed for powerful reasoning, agentic workflows, and versatile developer use cases. The series includes two main models: gpt-oss-120b, a 117-billion parameter model optimized for general-purpose, high-reasoning tasks that can run on a single H100 GPU, and gpt-oss-20b, a lighter 21-billion parameter model ideal for low-latency or specialized applications on smaller hardware. Both models use a native MXFP4 quantization for...
    Downloads: 9 This Week
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  • 2
    Transformer Debugger

    Transformer Debugger

    Tool for exploring and debugging transformer model behaviors

    Transformer Debugger (TDB) is a research tool developed by OpenAI’s Superalignment team to investigate and interpret the behaviors of small language models. It combines automated interpretability methods with sparse autoencoders, enabling researchers to analyze how specific neurons, attention heads, and latent features contribute to a model’s outputs. TDB allows users to intervene directly in the forward pass of a model and observe how such interventions change predictions, making it...
    Downloads: 2 This Week
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  • 3
    ChatGPT Retrieval Plugin

    ChatGPT Retrieval Plugin

    The ChatGPT Retrieval Plugin lets you easily find personal documents

    The chatgpt-retrieval-plugin repository implements a semantic retrieval backend that lets ChatGPT (or GPT-powered tools) access private or organizational documents in natural language by combining vector search, embedding models, and plugin infrastructure. It can serve as a custom GPT plugin or function-calling backend so that a chat session can “look up” relevant documents based on user queries, inject those results into context, and respond more knowledgeably about a private knowledge...
    Downloads: 1 This Week
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  • 4
    Anthropic SDK TypeScript

    Anthropic SDK TypeScript

    Access to Anthropic's safety-first language model APIs

    anthropic-sdk-typescript is the TypeScript / JavaScript client library for the Anthropic REST API, enabling backend or Node.js usage of models like Claude. It wraps API endpoints for creating messages, streaming responses, and managing parameters in a type-safe TS environment. The library is designed for server-side use, interfacing with REST, and is stable for integration in web services or backend agents. Example usage shows how to instantiate the Anthropic client, call...
    Downloads: 0 This Week
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  • 5
    Anthropic SDK Python

    Anthropic SDK Python

    Provides convenient access to the Anthropic REST API from any Python 3

    The anthropic-sdk-python repository is the official Python client library for interacting with the Anthropic (Claude) REST API. It is designed to provide a user-friendly, type-safe, and asynchronous/synchronous capable interface for making chat/completion requests to models like Claude. The library includes definitions for all request and response parameters using Python typed objects, automatically handles serialization and deserialization, and wraps HTTP logic (timeouts, retries, error...
    Downloads: 4 This Week
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  • 6
    MiMo-V2-Flash

    MiMo-V2-Flash

    MiMo-V2-Flash: Efficient Reasoning, Coding, and Agentic Foundation

    MiMo-V2-Flash is a large Mixture-of-Experts language model designed to deliver strong reasoning, coding, and agentic-task performance while keeping inference fast and cost-efficient. It uses an MoE setup where a very large total parameter count is available, but only a smaller subset is activated per token, which helps balance capability with runtime efficiency. The project positions the model for workflows that require tool use, multi-step planning, and higher throughput, rather than only...
    Downloads: 3 This Week
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  • 7
    FastViT

    FastViT

    This repository contains the official implementation of research

    FastViT is an efficient vision backbone family that blends convolutional inductive biases with transformer capacity to deliver strong accuracy at mobile and real-time inference budgets. Its design pursues a favorable latency-accuracy Pareto curve, targeting edge devices and server scenarios where throughput and tail latency matter. The models use lightweight attention and carefully engineered blocks to minimize token mixing costs while preserving representation power. Training and inference...
    Downloads: 0 This Week
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  • 8
    GLM-130B

    GLM-130B

    GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)

    GLM-130B is an open bilingual (English and Chinese) dense language model with 130 billion parameters, released by the Tsinghua KEG Lab and collaborators as part of the General Language Model (GLM) series. It is designed for large-scale inference and supports both left-to-right generation and blank filling, making it versatile across NLP tasks. Trained on over 400 billion tokens (200B English, 200B Chinese), it achieves performance surpassing GPT-3 175B, OPT-175B, and BLOOM-176B on multiple...
    Downloads: 4 This Week
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  • 9
    Grok-2.5

    Grok-2.5

    Large-scale xAI model for local inference with SGLang, Grok-2.5

    Grok-2.5 is a large-scale AI model developed and released by xAI in 2024, made available through Hugging Face for research and experimentation. The model is distributed as raw weights that require specialized infrastructure to run, rather than being hosted by inference providers. To use it, users must download over 500 GB of files and set them up locally with the SGLang inference engine. Grok-2.5 supports advanced inference with multi-GPU configurations, requiring at least 8 GPUs with more...
    Downloads: 0 This Week
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  • 10
    Mistral Large 3 675B Instruct 2512 Eagle

    Mistral Large 3 675B Instruct 2512 Eagle

    Speculative-decoding accelerator for the 675B Mistral Large 3

    Mistral Large 3 675B Instruct 2512 Eagle is the dedicated speculative-decoding draft model for the full Mistral Large 3 Instruct system, designed to significantly speed up generation while preserving high output quality. It works alongside the primary 675B instruct model, enabling faster response times by predicting several tokens ahead using Mistral’s Eagle speculative method. Built on the same frontier-scale multimodal Mixture-of-Experts architecture, it complements a system featuring 41B...
    Downloads: 0 This Week
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