#embeddings
SentenceTransformer.encode(docs)
it's best if we embed with smaller docs
and call it multiple times (rather than embedding more at once). On Colab T4, for gte-base-en-v1.5
, when embedding 1,000 docs of up to 8K chars each, here is the TOTAL time it took, based on batch sizes (lower is better) #embeddings
#embeddings
#gpu
#embeddings
#cloud
#embeddings
#embeddings
#image-generation
#embeddings
#markdown
#embeddings
It also supports text-to-image models like flux.dev and
speech recognition models like Whisper.#embeddings
#embeddings
#embeddings
#future
#gpu
#markdown
#models
#optimization
#prompt-engineering
#chatgpt
#embeddings
#gpu
#image-generation
#embeddings
#voice-cloning
unoti/voice-embeddings,
retkowsky/audio_embeddings,
pyannote/embedding (for speaker similarity),
and more.#embeddings
#embeddings
#ai-coding-tools
#embeddings
#gpu
#embeddings
text-embedding-3-large
which can be truncated. The embedding values have descending importance, so picking the first n is a good approximation. Also, gpt-3.5-turbo-0125
is 50% cheaper. #embeddings
#gpu
#embeddings
#future
#embeddings
#future
#tts
#voice-cloning
#embeddings
#embeddings
#search