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Cataloged from Accio-Lab/occamy-1.0-MLX-4bit
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Native MLX · group size 64 · 19.51 GB · text only
Candidate release — Mac Metal acceptance is pending. Linux native MLX validation passed. Mac inference, performance and broad model quality remain unverified.
File size is not the unified-memory requirement. Leave room for the operating system, KV cache and runtime buffers. Compare the 3-bit, 4-bit, 6-bit and 8-bit candidates in the MLX collection.
On Apple Silicon, install the versions used to create this export. The following is a usage recipe awaiting Mac Metal acceptance:
The stock CLI options below were checked with mlx-lm 0.31.3. Mac Metal acceptance remains pending. HTTP inference checks for this release are recorded only for the new 6-bit and 8-bit exports.
In a second terminal:
Client base URL: http://127.0.0.1:8000/v1. Inference runs on your machine.
A lossless adapter stacks separate expert weights in numeric expert order before invoking the Qwen3.5 sanitizer exactly once. Quantization and serialization use native APIs; reload uses the stock loader without an adapter.
Passed Linux checks: strict stock reload; complete stored floating-value checks; native dequantization of every quantized row; tokenizer/template comparison; and one bounded cached greedy CPU generation with finite logits. The prompt “Compute 2+2. Answer briefly.” returned 4. This is a limited smoke test, not a quality benchmark or a Mac runtime result.
Validation scope [blocked] · Artifact hashes [blocked] · Original model card
Apache 2.0, inherited from Occamy-1.0.
BF16 · GGUF · FP8 · NVFP4 · MLX 8-bit · MLX 6-bit · MLX 4-bit · MLX 3-bit · MTP head
Compare file sizes, validation scope and deployment commands in the checkpoint explorer.
8bit · 6bit · 5bit · 4bit · 3bit · mxfp8 · mxfp4 · nvfp4
The new 5-bit/MXFP4/MXFP8/NVFP4 cards include their own paired BF16 subset quality checks. Mac Metal acceptance remains pending.
python -m pip install "mlx==0.32.2" "mlx-lm==0.31.3"from mlx_lm import load, generate
model, tokenizer = load("Accio-Lab/occamy-1.0-MLX-4bit")messages = [{"role": "user", "content": "Compute 2+2. Answer briefly."}]prompt = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True, enable_thinking=False)response = generate(model, tokenizer, prompt=prompt, max_tokens=128)print(response)python -m pip install "mlx==0.32.2" "mlx-lm==0.31.3" "transformers==5.8.1"
mlx_lm.server --model Accio-Lab/occamy-1.0-MLX-4bit \ --host 127.0.0.1 --port 8000 \ --chat-template-args '{"enable_thinking":false}'curl http://127.0.0.1:8000/v1/chat/completions \ -H 'Content-Type: application/json' \ -d '{"model":"Accio-Lab/occamy-1.0-MLX-4bit","messages":[{"role":"user","content":"Compute 2+2. Answer briefly."}],"temperature":0,"max_tokens":128}'