Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results (legacy)
Doing the encoding using GPU
#7
by Luning-Yang - opened
I'm try to encode a massive amount of data using instructor. Here is what I did:
import torch
from transformers import AutoTokenizer
from InstructorEmbedding import INSTRUCTOR
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = INSTRUCTOR('hkunlp/instructor-large').to(device)
tokenizer = AutoTokenizer.from_pretrained('hkunlp/instructor-large')
However, I don't know how to properly convert the input data into tensors in order to use GPU for encoding. Could you elaborate on this?
Hi, Thanks a lot for your interest in the INSTRUCTOR model!
You may need to move both models and encoding texts to the GPU.
Feel free to add any questions or comments!