3 3 41

codito

https://codito.in

codito

AI & ML interests

None yet

Recent Activity

liked a model 7 days ago

stduhpf/google-gemma-3-12b-it-qat-q4_0-gguf-small

liked a dataset 6 months ago

nvidia/HelpSteer2

reacted to tomaarsen's post with 🔥 6 months ago

📣 Sentence Transformers v3.2.0 is out, marking the biggest release for inference in 2 years! 2 new backends for embedding models: ONNX (+ optimization & quantization) and OpenVINO, allowing for speedups up to 2x-3x AND Static Embeddings for 500x speedups at 10-20% accuracy cost. 1️⃣ ONNX Backend: This backend uses the ONNX Runtime to accelerate model inference on both CPU and GPU, reaching up to 1.4x-3x speedup depending on the precision. We also introduce 2 helper methods for optimizing and quantizing models for (much) faster inference. 2️⃣ OpenVINO Backend: This backend uses Intel their OpenVINO instead, outperforming ONNX in some situations on CPU. Usage is as simple as `SentenceTransformer("all-MiniLM-L6-v2", backend="onnx")`. Does your model not have an ONNX or OpenVINO file yet? No worries - it'll be autoexported for you. Thank me later 😉 🔒 Another major new feature is Static Embeddings: think word embeddings like GLoVe and word2vec, but modernized. Static Embeddings are bags of token embeddings that are summed together to create text embeddings, allowing for lightning-fast embeddings that don't require any neural networks. They're initialized in one of 2 ways: 1️⃣ via Model2Vec, a new technique for distilling any Sentence Transformer models into static embeddings. Either via a pre-distilled model with `from_model2vec` or with `from_distillation` where you do the distillation yourself. It'll only take 5 seconds on GPU & 2 minutes on CPU, no dataset needed. 2️⃣ Random initialization. This requires finetuning, but finetuning is extremely quick (e.g. I trained with 3 million pairs in 7 minutes). My final model was 6.6% worse than bge-base-en-v1.5, but 500x faster on CPU. Full release notes: https://github.com/UKPLab/sentence-transformers/releases/tag/v3.2.0 Documentation on Speeding up Inference: https://sbert.net/docs/sentence_transformer/usage/efficiency.html

View all activity

Organizations

None yet

codito's activity

New activity in bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF 9 months ago

Model responding with all GGGG

#3 opened 9 months ago by

YorkieOH10

New activity in bartowski/codegeex4-all-9b-GGUF 9 months ago

GGGGGGGGGGGGGGGGGGGGGGGGGGGG

#2 opened 9 months ago by

x4k

New activity in visheratin/MC-LLaVA-3b about 1 year ago

GGUF

#5 opened about 1 year ago by

codito