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nightscape/Intern-S2-Mobius-4bit-mlx
Intern-S2-Mobius-4bit-mlx is a text generation model from nightscape. Use it when you need the model to write or continue text. It is set up for mlx. The card lists the license as apache-2.0.
An MLX 4-bit (affine, group size 64) quantization of internlm/Intern-S2-Mobius — a 35B hybrid model: Gated-DeltaNet linear attention / full attention at interval 4, with 2560 experts in 4 globally-shared routed MoE ba…
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From the Hugging Face model README
An MLX 4-bit (affine, group size 64) quantization of internlm/Intern-S2-Mobius — a 35B hybrid model: Gated-DeltaNet linear attention / full attention at interval 4, with 2560 experts in 4 globally-shared routed MoE banks. Runs on Apple Silicon.
interns2_mobius (text_config.model_type = interns2_mobius_text), 40 layers, head_dim 256,
MoE 2560 experts / top-8, num_blocks 4. max_position_embeddings 262144.Requires the mlx-lm build that ships the interns2_mobius architecture
(official part of mlx-lm as of the model-support PR):
pip install -U mlx-lm
mlx_lm.generate --model nightscape/Intern-S2-Mobius-4bit-mlx \
-p "The secret to baking a good cake is" -m 1024 --trust-remote-code
--trust-remote-code is mandatory: the checkpoint bundles a custom tokenizer
(tokenization_interns1.py) and model code.
transformers does not yet ship interns2_mobius. The reference is the
upstream repo's trust_remote_code implementation, verified by full bf16 logit diff (argmax agreement
38/39, the sole miss a bit-identical tie).image-text-to-text,
but the MLX port loads the language model and generates text (no vision tower on this path).An experimental MTP (Multi-Token-Prediction) head is published separately:
nightscape/Intern-S2-Mobius-4bit-mlx-mtp.
It is consumed by the omlx server's interns2_mobius MTP driver, not by stock mlx-lm.
Weights and code under Apache-2.0 — see LICENSE. Model by InternLM; this is a derivative conversion of their weights plus the MLX port.