models/README.md

OpenMLE post-trained checkpoints

Both post-trained checkpoints are publicly downloadable from this repository:

Model	Path	Weight files
OpenMLE-30B	models/OpenMLE-30B/	12 safetensors shards
OpenMLE-35B	models/OpenMLE-35B/	15 language-model shards and model-vision-mtp.safetensors

Each directory includes the weight index, configuration, tokenizer and license files required to load that checkpoint. The 35B vision encoder and MTP components are inherited from its upstream base; the language-model weights were post-trained. Model weights use CC BY-NC 4.0; upstream components retain their Apache 2.0 terms and notices.

This is a dataset repository containing model files in subdirectories. Download only the desired checkpoint, then load its local directory:

from huggingface_hub import snapshot_download

root = snapshot_download(
    repo_id="nono314/openmle",
    repo_type="dataset",
    allow_patterns=["models/OpenMLE-30B/*"],
    local_dir="OpenMLE-release",
)
model_path = f"{root}/models/OpenMLE-30B"

For the 35B checkpoint, replace OpenMLE-30B with OpenMLE-35B. The respective Transformers architectures are Qwen3MoeForCausalLM and Qwen3_5MoeForConditionalGeneration; use a Transformers version supporting the selected architecture. Do not pass the dataset repository ID directly to from_pretrained; pass the downloaded model directory.

models/checksums.sha256 lists SHA-256 values for the model files. The supplementary ZIP contains code and data examples; these large weight files are hosted here and are not embedded in that ZIP.