Text Generation
MLX
Safetensors
deepseek_v4
apple-silicon
quantized
mixed-precision
axquant
axq
development
deepseek-v4
2bit
2-bit
mtp
Instructions to use AutomatosX/AX-DeepSeek-V4-Flash-MLX-AXQ-2bit-MTP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-DeepSeek-V4-Flash-MLX-AXQ-2bit-MTP 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("AutomatosX/AX-DeepSeek-V4-Flash-MLX-AXQ-2bit-MTP") 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 AutomatosX/AX-DeepSeek-V4-Flash-MLX-AXQ-2bit-MTP with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "AutomatosX/AX-DeepSeek-V4-Flash-MLX-AXQ-2bit-MTP" --prompt "Once upon a time"
- Atomic Chat
| { | |
| "created_at": "2026-08-08T10:35:22.594607Z", | |
| "dtypes": [ | |
| "BF16", | |
| "F32", | |
| "F8_E4M3", | |
| "F8_E8M0", | |
| "I8" | |
| ], | |
| "output": { | |
| "path": "mtp.safetensors", | |
| "sha256": "445e2f72d140a344ab3429b0a073ba2dc3f4198b40b0b7fe7ccc5bc41531806c", | |
| "size_bytes": 3593958116 | |
| }, | |
| "parameters": 6610048891, | |
| "role": "mtp", | |
| "schema_version": "axquant.protected-tensor-sidecar.v1", | |
| "source_files": [ | |
| { | |
| "path": "model-00046-of-00046.safetensors", | |
| "sha256": "f58f722893a6148216a2155cee4a57fe691cea4d3b323135c433a936b932055d", | |
| "size_bytes": 3593956092 | |
| } | |
| ], | |
| "source_model": { | |
| "architecture": "DeepseekV4ForCausalLM", | |
| "format": "mlx", | |
| "local_path": null, | |
| "model_id": "deepseek-ai/DeepSeek-V4-Flash", | |
| "revision": "60d8d70770c6776ff598c94bb586a859a38244f1" | |
| }, | |
| "tensor_count": 1575, | |
| "tensor_names_sha256": "5004dd518bc51fa41daefec6f8f5145b78bf8a96f788a17a7af255c484dd2777" | |
| } | |