サイト内検索
AI モデル 84757
- Intern-S2-Preview↗
internlm
- Jeff-1.1-Medium↗
jgeuter
- Qwen3.8-27B-NVFP4-vllm↗
kekzle
- MiniLM-L6-danish-encoder↗
KennethTM
*New version available, trained on more data and otherwise identical KennethTM/MiniLM-L6-danish-encoder-v2* This is a lightweight (~22 M parameters) sentence-transformers model for Danish NLP: It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for tasks like clustering or semantic search. The model was not pre-trained from scratch but adapted from the English version of sentence-transformers/all-MiniLM-L6-v2 with a Danish tokenizer.
- clap-htsat-unfused↗
laion
0. TL;DR 1. Model Details 2. Usage 3. Uses 4. Citation > Contrastive learning has shown remarkable success in the field of multimodal representation learning. In this paper, we propose a pipeline of contrastive language-audio pretraining to develop an audio representation by combining audio data with natural language descriptions. To accomplish this target, we first release LAION-Audio-630K, a large collection of 633,526 audio-text pairs from different data sources. Second, we construct a contrastive language-audio pretraining model by considering different audio encoders and text encoders. We incorporate the feature fusion mechanism and keyword-to-caption augmentation into the model design to further enable the model to process audio inputs of variable lengths and enhance the performance. Third, we perform comprehensive experiments to evaluate our model across three tasks: text-to-audio retrieval, zero-shot audio classification, and supervised audio classification. The results demonstrate that our model achieves superior performance in text-to-audio retrieval task. In audio classification tasks, the model achieves state-of-the-art performance in the zero-shot setting and is able to obtain performance comparable to models' results in the non-zero-shot setting. LAION-Audio-630K and the proposed model are both available to the public. You can use this model for zero shot audio classification or extracting audio and/or textual features.
- tamil-asr-qwen3↗
lemuralabs
- Magistral-Small-2509-ultra-uncensored-heretic-v2-GGUF↗
llmfan46
- Qwen3.6-35B-A3B-BUDGET-GGUF↗
lmcoleman
- deepseek-r1-8b-tool-merged↗
manishkumar2101114
- Qwen2.5-7B-Instruct-GGUF↗
MaziyarPanahi
- Model creator: Qwen - Original model: Qwen/Qwen2.5-7B-Instruct GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Here is an incomplete list of clients and libraries that are known to support GGUF: