File size: 1,051 Bytes
d2d2e7e 85a8e6f d2d2e7e 85a8e6f d2d2e7e 85a8e6f d2d2e7e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
---
library_name: transformers
license: apache-2.0
language:
- en
tags:
- fill-mask
- masked-lm
- long-context
- modernbert
- mlx
pipeline_tag: fill-mask
inference: false
---
# mlx-community/answerdotai-ModernBERT-base-4bit
The Model [mlx-community/answerdotai-ModernBERT-base-4bit](https://huggingface.co/mlx-community/answerdotai-ModernBERT-base-4bit) was converted to MLX format from [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) using mlx-lm version **0.0.3**.
## Use with mlx
```bash
pip install mlx-embeddings
```
```python
from mlx_embeddings import load, generate
import mlx.core as mx
model, tokenizer = load("mlx-community/answerdotai-ModernBERT-base-4bit")
# 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)
```
|