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--- |
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language: |
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- en |
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tags: |
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- sentence-transformers |
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- sentence-similarity |
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- feature-extraction |
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- generated_from_trainer |
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- dataset_size:6661966 |
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- loss:MultipleNegativesRankingLoss |
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- loss:CachedMultipleNegativesRankingLoss |
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- loss:SoftmaxLoss |
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- loss:AnglELoss |
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- loss:CoSENTLoss |
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- loss:CosineSimilarityLoss |
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- mlx |
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base_model: answerdotai/ModernBERT-base |
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widget: |
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- source_sentence: Daniel went to the kitchen. Sandra went back to the kitchen. Daniel |
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moved to the garden. Sandra grabbed the apple. Sandra went back to the office. |
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Sandra dropped the apple. Sandra went to the garden. Sandra went back to the bedroom. |
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Sandra went back to the office. Mary went back to the office. Daniel moved to |
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the bathroom. Sandra grabbed the apple. Sandra travelled to the garden. Sandra |
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put down the apple there. Mary went back to the bathroom. Daniel travelled to |
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the garden. Mary took the milk. Sandra grabbed the apple. Mary left the milk there. |
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Sandra journeyed to the bedroom. John travelled to the office. John went back |
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to the garden. Sandra journeyed to the garden. Mary grabbed the milk. Mary left |
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the milk. Mary grabbed the milk. Mary went to the hallway. John moved to the hallway. |
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Mary picked up the football. Sandra journeyed to the kitchen. Sandra left the |
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apple. Mary discarded the milk. John journeyed to the garden. Mary dropped the |
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football. Daniel moved to the bathroom. Daniel journeyed to the kitchen. Mary |
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travelled to the bathroom. Daniel went to the bedroom. Mary went to the hallway. |
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Sandra got the apple. Sandra went back to the hallway. Mary moved to the kitchen. |
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Sandra dropped the apple there. Sandra grabbed the milk. Sandra journeyed to the |
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bathroom. John went back to the kitchen. Sandra went to the kitchen. Sandra travelled |
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to the bathroom. Daniel went to the garden. Daniel moved to the kitchen. Sandra |
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dropped the milk. Sandra got the milk. Sandra put down the milk. John journeyed |
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to the garden. Sandra went back to the hallway. Sandra picked up the apple. Sandra |
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got the football. Sandra moved to the garden. Daniel moved to the bathroom. Daniel |
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travelled to the garden. Sandra went back to the bathroom. Sandra discarded the |
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football. |
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sentences: |
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- In the adulthood stage, it can jump, walk, run |
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- The chocolate is bigger than the container. |
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- The football before the bathroom was in the garden. |
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- source_sentence: Almost everywhere the series converges then . |
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sentences: |
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- The series then converges almost everywhere . |
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- Scrivener dated the manuscript to the 12th century , C. R. Gregory to the 13th |
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century . Currently the manuscript is dated by the INTF to the 12th century . |
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- Both daughters died before he did , Tosca in 1976 and Janear in 1981 . |
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- source_sentence: how are you i'm doing good thank you you im not good having cough |
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and colg |
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sentences: |
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- 'This example tweet expresses the emotion: happiness' |
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- This example utterance is about cooking recipies. |
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- This example text from a US presidential speech is about macroeconomics |
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- source_sentence: A man is doing pull-ups |
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sentences: |
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- The man is doing exercises in a gym |
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- A black and white dog with a large branch is running in the field |
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- There is no man drawing |
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- source_sentence: A chef is preparing some food |
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sentences: |
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- The man is lifting weights |
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- A chef is preparing a meal |
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- A dog is in a sandy area with the sand that is being stirred up into the air and |
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several plants are in the background |
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datasets: |
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- tomaarsen/natural-questions-hard-negatives |
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- tomaarsen/gooaq-hard-negatives |
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- bclavie/msmarco-500k-triplets |
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- sentence-transformers/all-nli |
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- sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1 |
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- sentence-transformers/gooaq |
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- sentence-transformers/natural-questions |
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- tasksource/merged-2l-nli |
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- tasksource/merged-3l-nli |
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- tasksource/zero-shot-label-nli |
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- MoritzLaurer/dataset_train_nli |
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- google-research-datasets/paws |
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- nyu-mll/glue |
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- mwong/fever-evidence-related |
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- tasksource/sts-companion |
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pipeline_tag: sentence-similarity |
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library_name: sentence-transformers |
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--- |
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# mlx-community/tasksource-ModernBERT-base-embed-bf16 |
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The Model [mlx-community/tasksource-ModernBERT-base-embed-bf16](https://huggingface.co/mlx-community/tasksource-ModernBERT-base-embed-bf16) was converted to MLX format from [tasksource/ModernBERT-base-embed](https://huggingface.co/tasksource/ModernBERT-base-embed) using mlx-lm version **0.0.3**. |
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## Use with mlx |
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```bash |
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pip install mlx-embeddings |
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``` |
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```python |
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from mlx_embeddings import load, generate |
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import mlx.core as mx |
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model, tokenizer = load("mlx-community/tasksource-ModernBERT-base-embed-bf16") |
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# For text embeddings |
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output = generate(model, processor, texts=["I like grapes", "I like fruits"]) |
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embeddings = output.text_embeds # Normalized embeddings |
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# Compute dot product between normalized embeddings |
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similarity_matrix = mx.matmul(embeddings, embeddings.T) |
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print("Similarity matrix between texts:") |
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print(similarity_matrix) |
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``` |
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