Instructions to use inferencerlabs/IQuest-Coder-V1-40B-Instruct-MLX-Q6.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use inferencerlabs/IQuest-Coder-V1-40B-Instruct-MLX-Q6.5 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("inferencerlabs/IQuest-Coder-V1-40B-Instruct-MLX-Q6.5") 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 inferencerlabs/IQuest-Coder-V1-40B-Instruct-MLX-Q6.5 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "inferencerlabs/IQuest-Coder-V1-40B-Instruct-MLX-Q6.5" --prompt "Once upon a time"
NOTICE
No longer available on HF due to storage restrictions - archived here
INFORMATION
See IQuest-Coder-V1-40B-Instruct MLX in action - demonstration video
q6.5bit mixed quant typically achieves 1.128 perplexity in our testing
| Quantization | Perplexity |
|---|---|
| q2.5 | 41.293 |
| q3.5 | 1.900 |
| q4.5 | 1.168 |
| q4.8 | 1.140 |
| q5.5 | 1.141 |
| q6.5 | 1.128 |
| q8.5 | 1.128 |
Usage Notes
Tested on a M3 Ultra using Inferencer app v1.9.1
- Single inference ~18.5 tokens/s @ 1000 tokens
- Batched inference ~30 total tokens/s across two inferences
- Memory usage: ~30 GB
Quantized with a modified version of MLX 0.30
For more details see demonstration video or visit IQuest-Coder-V1-40B-Instruct.
Model tree for inferencerlabs/IQuest-Coder-V1-40B-Instruct-MLX-Q6.5
Base model
IQuestLab/IQuest-Coder-V1-40B-Instruct