mlx-community
/

tasksource-ModernBERT-base-embed-4bit

Sentence Similarity

sentence-transformers

feature-extraction

Generated from Trainer

dataset_size:6661966

loss:MultipleNegativesRankingLoss

loss:CachedMultipleNegativesRankingLoss

loss:SoftmaxLoss

loss:CoSENTLoss

loss:CosineSimilarityLoss

Model card Files Files and versions Community

prince-canuma commited on 22 days ago

Commit

867d844

·

verified ·

1 Parent(s): e8e4409

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@@ -88,7 +88,7 @@ library_name: sentence-transformers
 # mlx-community/ModernBERT-base-embed-4bit
-The Model [mlx-community/ModernBERT-base-embed-4bit](https://huggingface.co/mlx-community/ModernBERT-base-embed-4bit) was converted to MLX format from [tasksource/ModernBERT-base-embed](https://huggingface.co/tasksource/ModernBERT-base-embed) using mlx-lm version **0.0.3**.
 ## Use with mlx
@@ -100,7 +100,7 @@ pip install mlx-embeddings
 from mlx_embeddings import load, generate
 import mlx.core as mx
-model, tokenizer = load("mlx-community/ModernBERT-base-embed-4bit")
 # For text embeddings
 output = generate(model, processor, texts=["I like grapes", "I like fruits"])

 # mlx-community/ModernBERT-base-embed-4bit
+The Model [mlx-community/tasksource-ModernBERT-base-embed-4bit](https://huggingface.co/mlx-community/tasksource-ModernBERT-base-embed-4bit) was converted to MLX format from [tasksource/ModernBERT-base-embed](https://huggingface.co/tasksource/ModernBERT-base-embed) using mlx-lm version **0.0.3**.
 ## Use with mlx
 from mlx_embeddings import load, generate
 import mlx.core as mx
+model, tokenizer = load("mlx-community/tasksource-ModernBERT-base-embed-4bit")
 # For text embeddings
 output = generate(model, processor, texts=["I like grapes", "I like fruits"])