Instructions to use upadhyay/sql-4bit-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use upadhyay/sql-4bit-1k with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("upadhyay/sql-4bit-1k") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use upadhyay/sql-4bit-1k with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "upadhyay/sql-4bit-1k" --prompt "Once upon a time"
- Atomic Chat
File size: 606 Bytes
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language:
- en
license: apache-2.0
pipeline_tag: text-generation
tags:
- pretrained
- mlx
inference:
parameters:
temperature: 0.7
---
# upadhyay/sql-4bit-1k
The Model [upadhyay/sql-4bit-1k](https://huggingface.co/upadhyay/sql-4bit-1k) was converted to MLX format from [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) using mlx-lm version **0.15.2**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("upadhyay/sql-4bit-1k")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
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