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9dc9951394589b93a790b06d2f24f8e8e168385e · commit on GitHub
huggingface-blog-feed: changed (263265 bytes, HTTP 200)
raw/huggingface-blog-feed/response.xml modified
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@@ -6,6 +6,12 @@ <link>https://huggingface.co/blog</link> <description>The Hugging Face blog</description> <language>en-US</language>+
<item>+
<title>NVIDIA Nemotron 3.5 Transcribe and Granary v2: Intelligent Multilingual Transcription You Can Prompt and Adapt</title>+
<pubDate>Wed, 28 Oct 2026 14:58:17 GMT</pubDate>+
<link>https://huggingface.co/blog/nvidia/nemotron-transcribe-granary</link>+
<guid isPermaLink="false">https://huggingface.co/blog/nvidia/nemotron-transcribe-granary</guid>+
</item> <item> <title>Build specialized multimodal models with LFM3</title> <pubDate>Tue, 27 Oct 2026 17:16:52 GMT</pubDate>@
@@ -36,12 +42,6 @@ <link>https://huggingface.co/blog/ibm-research/granite-timeseries-ensemble-r1</link> <guid isPermaLink="false">https://huggingface.co/blog/ibm-research/granite-timeseries-ensemble-r1</guid> </item>-
<item>-
<title>NVIDIA Kumo Relational Outperforms Supervised Machine Learning on Relational Data, No Training Required</title>-
<pubDate>Wed, 21 Oct 2026 18:26:30 GMT</pubDate>-
<link>https://huggingface.co/blog/nvidia/kumo-relational</link>-
<guid isPermaLink="false">https://huggingface.co/blog/nvidia/kumo-relational</guid>-
</item> <item> <title>How Specializing the Vocabulary of SLMs Can Cut Inference Cost by 77% in Real Applications</title> <pubDate>Wed, 21 Oct 2026 17:35:36 GMT</pubDate>