New MTP models not supported
Post from Google about new MTP models: https://blog.google/innovation-and-ai/technology/developers-tools/multi-token-prediction-gemma-4/ HF link to models: https://huggingface.co/collections/mlx-community/gemma-4-assistant-mtp Simple script to download and prompt the model: ``` from mlx_lm import load, generate model, tokenizer = load("mlx-community/gemma-4-31B-it-assistant-bf16") messages = [{"role": "user", "content": "Explain quantum entanglement simply."}] prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False) response = generate(model, tokenizer, prompt=prompt, max_tokens=512, verbose=True) ``` Resulting error: ValueError: Model type gemma4_assistant not supported.
Posted by danielringwald on May 8, 2026, 8:14 AM
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struct's lifetime requirements can be bypassed via covariant field assignment
Proposal to Reorganize the Moderation Team and Review Moderation Policies
Progressive FPS degradation appears to be related to dota2.com — blocking the domain prevents the performance loss
proposal: container/...: generic collection types
Better Custom Endpoint BYOK
A concrete policy for backward compatibility until Godot 5.0
New MTP models not supported
Tracking: 429 / Capacity Issues
New MTP models not supported
Post from Google about new MTP models: https://blog.google/innovation-and-ai/technology/developers-tools/multi-token-prediction-gemma-4/ HF link to models: https://huggingface.co/collections/mlx-community/gemma-4-assistant-mtp Simple script to download and prompt the model: ``` from mlx_lm import load, generate model, tokenizer = load("mlx-community/gemma-4-31B-it-assistant-bf16") messages = [{"role": "user", "content": "Explain quantum entanglement simply."}] prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False) response = generate(model, tokenizer, prompt=prompt, max_tokens=512, verbose=True) ``` Resulting error: ValueError: Model type gemma4_assistant not supported.
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