Mixed-precision quantized version of
Qwen/Qwen3.5-35B-A3B optimised by
baa.ai using a proprietary Black Sheep AI method.
Per-tensor bit-width allocation via advanced sensitivity analysis and budget-constrained optimisation — no calibration data required.
1from mlx_lm import load, generate
2
3model, tokenizer = load("baa-ai/Qwen3.5-35B-A3B-RAM-17GB-MLX")
4response = generate(model, tokenizer, prompt="Hello!", max_tokens=256)
5print(response)
1prompt = tokenizer.apply_chat_template(
2 [{"role": "user", "content": "Write a Python function that reverses a string."}],
3 tokenize=False,
4 add_generation_prompt=True,
5 enable_thinking=False,
6)
7response = generate(model, tokenizer, prompt=prompt, max_tokens=2048)
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Watchman — Capability audit and governance platform for compressed AI models. Know exactly what your quantized model can do before it goes live. Watchman predicts which capabilities survive compression in minutes — replacing weeks of benchmarking. Includes compliance-ready reporting for regulated industries, quality valley warnings for counterproductive memory allocations, instant regression diagnosis tracing issues to specific tensors, and 22 adversarial security probes scanning for injection, leakage, hallucination, and code vulnerabilities.
