metadata
language:
- en
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:6661966
- loss:MultipleNegativesRankingLoss
- loss:CachedMultipleNegativesRankingLoss
- loss:SoftmaxLoss
- loss:AnglELoss
- loss:CoSENTLoss
- loss:CosineSimilarityLoss
- mlx
base_model: answerdotai/ModernBERT-base
widget:
- source_sentence: >-
Daniel went to the kitchen. Sandra went back to the kitchen. Daniel moved
to the garden. Sandra grabbed the apple. Sandra went back to the office.
Sandra dropped the apple. Sandra went to the garden. Sandra went back to
the bedroom. Sandra went back to the office. Mary went back to the office.
Daniel moved to the bathroom. Sandra grabbed the apple. Sandra travelled
to the garden. Sandra put down the apple there. Mary went back to the
bathroom. Daniel travelled to the garden. Mary took the milk. Sandra
grabbed the apple. Mary left the milk there. Sandra journeyed to the
bedroom. John travelled to the office. John went back to the garden.
Sandra journeyed to the garden. Mary grabbed the milk. Mary left the milk.
Mary grabbed the milk. Mary went to the hallway. John moved to the
hallway. Mary picked up the football. Sandra journeyed to the kitchen.
Sandra left the apple. Mary discarded the milk. John journeyed to the
garden. Mary dropped the football. Daniel moved to the bathroom. Daniel
journeyed to the kitchen. Mary travelled to the bathroom. Daniel went to
the bedroom. Mary went to the hallway. Sandra got the apple. Sandra went
back to the hallway. Mary moved to the kitchen. Sandra dropped the apple
there. Sandra grabbed the milk. Sandra journeyed to the bathroom. John
went back to the kitchen. Sandra went to the kitchen. Sandra travelled to
the bathroom. Daniel went to the garden. Daniel moved to the kitchen.
Sandra dropped the milk. Sandra got the milk. Sandra put down the milk.
John journeyed to the garden. Sandra went back to the hallway. Sandra
picked up the apple. Sandra got the football. Sandra moved to the garden.
Daniel moved to the bathroom. Daniel travelled to the garden. Sandra went
back to the bathroom. Sandra discarded the football.
sentences:
- In the adulthood stage, it can jump, walk, run
- The chocolate is bigger than the container.
- The football before the bathroom was in the garden.
- source_sentence: Almost everywhere the series converges then .
sentences:
- The series then converges almost everywhere .
- >-
Scrivener dated the manuscript to the 12th century , C. R. Gregory to
the 13th century . Currently the manuscript is dated by the INTF to the
12th century .
- Both daughters died before he did , Tosca in 1976 and Janear in 1981 .
- source_sentence: >-
how are you i'm doing good thank you you im not good having cough and
colg
sentences:
- 'This example tweet expresses the emotion: happiness'
- This example utterance is about cooking recipies.
- This example text from a US presidential speech is about macroeconomics
- source_sentence: A man is doing pull-ups
sentences:
- The man is doing exercises in a gym
- A black and white dog with a large branch is running in the field
- There is no man drawing
- source_sentence: A chef is preparing some food
sentences:
- The man is lifting weights
- A chef is preparing a meal
- >-
A dog is in a sandy area with the sand that is being stirred up into the
air and several plants are in the background
datasets:
- tomaarsen/natural-questions-hard-negatives
- tomaarsen/gooaq-hard-negatives
- bclavie/msmarco-500k-triplets
- sentence-transformers/all-nli
- sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1
- sentence-transformers/gooaq
- sentence-transformers/natural-questions
- tasksource/merged-2l-nli
- tasksource/merged-3l-nli
- tasksource/zero-shot-label-nli
- MoritzLaurer/dataset_train_nli
- google-research-datasets/paws
- nyu-mll/glue
- mwong/fever-evidence-related
- tasksource/sts-companion
pipeline_tag: sentence-similarity
library_name: sentence-transformers
mlx-community/tasksource-ModernBERT-base-embed-8bit
The Model mlx-community/tasksource-ModernBERT-base-embed-8bit was converted to MLX format from tasksource/ModernBERT-base-embed using mlx-lm version 0.0.3.
Use with mlx
pip install mlx-embeddings
from mlx_embeddings import load, generate
import mlx.core as mx
model, tokenizer = load("mlx-community/tasksource-ModernBERT-base-embed-8bit")
# For text embeddings
output = generate(model, processor, texts=["I like grapes", "I like fruits"])
embeddings = output.text_embeds # Normalized embeddings
# Compute dot product between normalized embeddings
similarity_matrix = mx.matmul(embeddings, embeddings.T)
print("Similarity matrix between texts:")
print(similarity_matrix)