README.md

---
license: cc-by-nc-4.0
language:
- en
- multilingual
base_model: zeroentropy/zembed-1-embedding
pipeline_tag: feature-extraction
tags:
- finance
- legal
- healthcare
- code
- stem
- medical
- multilingual
- mlx
- mlx-my-repo
library_name: sentence-transformers
model_max_length: 32768
---

# lexrivera/zembed-1-embedding-mlx-6Bit

The Model [lexrivera/zembed-1-embedding-mlx-6Bit](https://huggingface.co/lexrivera/zembed-1-embedding-mlx-6Bit) was converted to MLX format from [zeroentropy/zembed-1-embedding](https://huggingface.co/zeroentropy/zembed-1-embedding) using mlx-lm version **0.31.2**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("lexrivera/zembed-1-embedding-mlx-6Bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
```