Zera-24B-4bit
Zera is a 24B-parameter, 4-bit MLX language model fine-tuned for coding, debugging, technical explanations, general conversation, grammar, and vocabulary. It is a standalone fused model: users do not need a separate adapter.
Use with MLX
pip install mlx-lm
from mlx_lm import generate, load
model, tokenizer = load("Zexiry/Zera-24B-4bit")
messages = [{"role": "user", "content": "Introduce yourself, then write a Python trie."}]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
print(generate(model, tokenizer, prompt=prompt, max_tokens=800, verbose=False))
Zera's default chat template supplies its assistant identity when an application does not provide a system prompt. Applications can still provide their own system prompt normally.
Technical details
- Parameters: 23.57B
- Weight format: MLX 4-bit, group size 64
- Fine-tuning: QLoRA, rank 32, 24 adapted layers
- License: Apache-2.0
The base_model metadata above is retained for reproducibility, attribution, and
license compliance. In conversation, the assistant identity is Zera.
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Model size
24B params
Tensor type
U32
·
BF16 ·
Hardware compatibility
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4-bit
Model tree for Zexiry/Zera-24B-4bit
Base model
mistralai/Mistral-Small-3.1-24B-Base-2503 Finetuned
mistralai/Devstral-Small-2507 Finetuned
mlx-community/Devstral-Samll-2507-bf16 Quantized
mlx-community/Devstral-Small-2507-4bit