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Hugging Face Transformers

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  • Transformers now runs llama.cpp quants

    We’re on a journey to advance and democratize artificial intelligence through open source and open science.

    Hugging Face Blog11 min read

  • Release 5.17.0

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Release 5.17.0 · huggingface/transformers

    Transformers15 min read

  • RAG Evaluation with Prometheus 2

    Evaluating the responses of Language Models and LLM-based applications often involves using model-based metrics that do not require ground truth labels.

    Haystack by deepset28 min read

  • NeoMME: an efficient Multimodal-native and Multilingual Encoder

    We introduce NeoMME, a family of 260M and 800M multilingual multimodal encoders. Unlike many generative visual language models, NeoMME does not use a separate pretrained vision tower or a causal language model.

    Hugging Face Blog11 min read

  • Release: v5.16.0

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Release: v5.16.0 · huggingface/transformers

    Transformers17 min read

  • Release v5.16.1

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Release v5.16.1 · huggingface/transformers

    Transformers1 min read

  • Granite 4.2 LLMs: How They're Built

    TL;DR: Granite 4.2 is our first family of dense, decoder-only reasoning LLMs, released in three sizes: 3B, 8B, and 30B. These models are post-trained from Granite-4.1 base models.

    Hugging Face Blog21 min read

  • Patch release: v5.15.1

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Patch release: v5.15.1 · huggingface/transformers

    Transformers1 min read

  • Release: v5.15.0

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Release: v5.15.0 · huggingface/transformers

    Transformers20 min read

  • Patch release: v5.14.1

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Patch release: v5.14.1 · huggingface/transformers

    Transformers1 min read

  • Release v5.14.0

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Release v5.14.0 · huggingface/transformers

    Transformers8 min read

  • Patch release v5.13.1

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Patch release v5.13.1 · huggingface/transformers

    Transformers1 min read

  • Release v5.13.0

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Release v5.13.0 · huggingface/transformers

    Transformers19 min read

  • Running PII detection locally with the Rampart NER model

    How Arcjet added an optional on-device model backend for sensitive information detection: a pluggable rule interface, deterministic recognizers for structured data, offset reconstruction for token-classification output, and local ONNX inference in the request path.

    Arcjet Blog11 min read

  • Patch release v5.12.1

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Patch release v5.12.1 · huggingface/transformers

    Transformers1 min read

  • Fine Tuning LLMs - A Practical Guide

    Learn how to fine-tune large language models for specific needs. A practical guide covering techniques, tools, and best practices.

    VoltAgent Blog9 min read

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