Thenlper: GTE-Large
- by thenlper
- thenlper/gte-large
The gte-large embedding model converts English sentences, paragraphs and moderate-length documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for information retrieval, semantic textual similarity, reranking and...
What the numbers mean
- Context window512 tokens
- How much the model can read in one request, counting your prompt, any files and the conversation so far. That is about 384 words, or 1 pages.
- Max output460 tokens
- The longest single reply it can write: about 345 words.
- Input price$0.01 per million tokens
- What you pay for everything the model reads. A 1,000-word prompt costs less than a cent.
- Output priceFree
- What you pay for everything the model writes. Output usually costs more than input. A 500-word answer costs nothing.
- Modalitiestext in, embeddings out
- The kinds of content it accepts and the kinds it produces. A model that takes images in can read a screenshot; one that only puts text out cannot draw.