Microsoft has released HARC-Qwen2.5-7B-Instruct, a fine-tuned version of Qwen2.5-7B-Instruct optimized for safety and alignment in conversational AI. The model is a transformer-based text-generation model, available on Hugging Face under the Apache 2.0 license. It is distributed in safetensors format and is compatible with text-generation-inference and Hugging Face endpoints. The release is associated with the paper arXiv:2607.00572.
Microsoft released HARC-Llama-3.1-8B-Instruct on Hugging Face. It is a text-generation model built on Meta's Llama 3.1 8B Instruct. Repository tags indicate a focus on safety, alignment, and conversational use. The model card provides no benchmarks, training details, or specific capability claims. It is distributed under the Llama 3.1 license.
Nvidia has published a quantized variant of the Mistral-Medium-3.5-128B large language model on Hugging Face. The model employs NVFP4, a 4-bit floating point precision format, to reduce memory footprint and potentially accelerate inference. It is labeled as conversational and text-generation compatible, using the safetensors format. The repository indicates the model is based on the original Mistral-Medium-3.5-128B from Mistral AI and is shared under a custom license.
Microsoft has released GELab-Zero-4B-preview-Sico-Evolution, a 4-billion-parameter vision-language model specialized for GUI agent tasks. The model is built on Qwen3-VL using LoRA fine-tuning and targets mobile and general GUI agent use cases. It supports English and Chinese text inputs, and processes image-text-to-text pipelines. The release is open-source under the Apache 2.0 license and is noted as an early preview version.
A Hugging Face repository for the LongCat-2.0 model by meituan-longcat was created on June 30, 2026. The repository metadata contains no description of the model's architecture, capabilities, or usage. As of the creation timestamp, the repository has 51 likes and 0 downloads.
Google has published the tabfm-1.0.0-pytorch model repository on Hugging Face. The model is tagged as 'tabfm', suggesting a tabular foundation model. No further details about architecture, training data, or intended use are provided in the repository. The license is listed as 'other'. Downloads and likes are minimal at the time of the snapshot.