metadata
license: apache-2.0
base_model:
- sentence-transformers/all-MiniLM-L6-v2
**This model is a neuron compiled version of https://huggingface.co./sentence-transformers/all-MiniLM-L6-v2 ***
It was compiled on version 2.20 of the Neuron SDK. You may need to run the compilation process again.
See https://huggingface.co./docs/optimum-neuron/en/inference_tutorials/sentence_transformers for more details
For information on how to run on SageMaker: https://huggingface.co./docs/optimum-neuron/en/inference_tutorials/sentence_transformers
To run:
from optimum.neuron import NeuronModelForSentenceTransformers
from transformers import AutoTokenizer
model_id = "jburtoft/all-MiniLM-L6-v2-neuron"
# Use the line below if you have to compile the model yourself
#model_id = "all-MiniLM-L6-v2-neuron"
model = NeuronModelForSentenceTransformers.from_pretrained(model_id)
tokenizer = AutoTokenizer.from_pretrained(model_id)
# Run inference
prompt = "I like to eat apples"
encoded_input = tokenizer(prompt, return_tensors='pt')
outputs = model(**encoded_input)
token_embeddings = outputs.token_embeddings
sentence_embedding = outputs.sentence_embedding
print(f"token embeddings: {token_embeddings.shape}") # torch.Size([1, 7, 384])
print(f"sentence_embedding: {sentence_embedding.shape}") # torch.Size([1, 384])
To compile:
optimum-cli export neuron -m sentence-transformers/all-MiniLM-L6-v2 --sequence_length 512 --batch_size 1 --task feature-extraction all-MiniLM-L6-v2-neuron