Instructions to use ukisai/Swift-1.5-5bit-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ukisai/Swift-1.5-5bit-MLX with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("ukisai/Swift-1.5-5bit-MLX") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use ukisai/Swift-1.5-5bit-MLX with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "ukisai/Swift-1.5-5bit-MLX"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "ukisai/Swift-1.5-5bit-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use ukisai/Swift-1.5-5bit-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "ukisai/Swift-1.5-5bit-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "ukisai/Swift-1.5-5bit-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ukisai/Swift-1.5-5bit-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use ukisai/Swift-1.5-5bit-MLX with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "ukisai/Swift-1.5-5bit-MLX"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default ukisai/Swift-1.5-5bit-MLX
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use ukisai/Swift-1.5-5bit-MLX with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "ukisai/Swift-1.5-5bit-MLX"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "ukisai/Swift-1.5-5bit-MLX" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download compatibility/quant-validation-results.json from ukisai/Swift-1.5-5bit-MLX: direct link, hf CLI and curl.
- Browser
- Download file 3.78 kB
-
https://huggingface.co/ukisai/Swift-1.5-5bit-MLX/resolve/main/compatibility/quant-validation-results.json
- Command line
-
hf download hf://ukisai/Swift-1.5-5bit-MLX/compatibility/quant-validation-results.json
-
curl -L -o quant-validation-results.json https://huggingface.co/ukisai/Swift-1.5-5bit-MLX/resolve/main/compatibility/quant-validation-results.json
3.78 kB
| { | |
| "all_floating_tensors_finite": true, | |
| "assets_sha256": { | |
| "chat_template.jinja": "c3cf9e34abf4f9e36c2d72165aa9c132d3e2a725b6c2586aaa3a8af9d7a81041", | |
| "generation_config.json": "e70c136c1b78ddc1fb0905bac8e733a4dc448d4f852a5dd75143fffc70be550e", | |
| "merges.txt": "a9d356d7bdf1ef4949e3e748e95b8e10ad9d4e2e838eddc38a0a7b6b94d1db8d", | |
| "preprocessor_config.json": "27225450ac9c6529872ee1924fcb0962ff5634834f817040f444118116f4e516", | |
| "tokenizer.json": "0997f410c57a1f4e53b09e4be8f4a172d90edd9564368fb0847030937229b9f3", | |
| "tokenizer_config.json": "b11349aafa7cdc6a320767cf7ceb29ed82f7eda5d65e8e0819e76f0ce947bf27", | |
| "video_preprocessor_config.json": "7768af27c1fafa9cc9011c1dc20067e03f8915e03b63504550e11d5066986d13", | |
| "vocab.json": "ce99b4cb2983d118806ce0a8b777a35b093e2000a503ebde25853284c9dfa003" | |
| }, | |
| "categories": { | |
| "MTP": 15, | |
| "text": 851, | |
| "vision": 333 | |
| }, | |
| "chat_templates": [ | |
| { | |
| "options": { | |
| "enable_thinking": false | |
| }, | |
| "rendered": "<|im_start|>user\nSay hello.<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n" | |
| }, | |
| { | |
| "options": { | |
| "reasoning_effort": "low" | |
| }, | |
| "rendered": "<|im_start|>system\nReasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.<|im_end|>\n<|im_start|>user\nSay hello.<|im_end|>\n<|im_start|>assistant\n<think>\n" | |
| }, | |
| { | |
| "options": { | |
| "reasoning_effort": "xhigh" | |
| }, | |
| "rendered": "<|im_start|>system\nReasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.<|im_end|>\n<|im_start|>user\nSay hello.<|im_end|>\n<|im_start|>assistant\n<think>\n" | |
| } | |
| ], | |
| "exact_unquantized_tensors": 609, | |
| "generation": { | |
| "elapsed_seconds": 495.4394222159999, | |
| "finish_reason": "stop", | |
| "prompt": "<|im_start|>user\nReply with exactly: Hello from Swift.<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n", | |
| "prompt_tokens_per_second": 0.04886516458777248, | |
| "text": "Hello from Swift.", | |
| "token_ids": [ | |
| 9419, | |
| 494, | |
| 22929, | |
| 13, | |
| 248046 | |
| ], | |
| "tokens": 5, | |
| "tokens_per_second": 0.05894060179705689 | |
| }, | |
| "ignored_tensors": 0, | |
| "inference_floating_dtype": "float32, CPU runtime only; stored floating tensors remain BF16", | |
| "load_memory_bytes": 19281804392, | |
| "load_seconds": 3.1353140849996635, | |
| "mapped_source_tensors": 1199, | |
| "mtp": { | |
| "path": "Explicit MTP step with real text hidden states and shared LM head; speculative generation is not integrated", | |
| "shape": [ | |
| 1, | |
| 1, | |
| 248320 | |
| ], | |
| "status": "PASS" | |
| }, | |
| "native_bf16_cpu_inference": "Aborted after reproducing incorrect accumulation in the official Linux BF16 quantized matmul. See cpu-quantized-matmul-diagnostic.json.", | |
| "process_peak_rss_bytes": 24964259840, | |
| "processor": "Qwen3VLProcessor", | |
| "quantization": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "recorded_at": "2026-09-22T12:17:07.052752+00:00", | |
| "saved_tensors": 2379, | |
| "source_repo": "ukisai/Swift-1.5-Qwen3.8-27b", | |
| "source_revision": "5ad04445d2686f525e9fbe5c077e6fa0c7df4200", | |
| "source_shard_bytes": 55563006776, | |
| "source_shards": 18, | |
| "source_tensors": 1199, | |
| "status": "PASS", | |
| "tokenizer": "Qwen2Tokenizer", | |
| "total_validation_seconds": 609.2779944080003, | |
| "unexplained_tensors": 0, | |
| "vision": { | |
| "grid": [ | |
| [ | |
| 1, | |
| 16, | |
| 16 | |
| ] | |
| ], | |
| "path": "Vision encoder only; image/video insertion and multimodal text generation are not implemented", | |
| "shape": [ | |
| 64, | |
| 5120 | |
| ], | |
| "status": "PASS" | |
| } | |
| } | |