Instructions to use blazeofchi/mempool-qwen-logits-orchestrator-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blazeofchi/mempool-qwen-logits-orchestrator-v0 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("blazeofchi/mempool-qwen-logits-orchestrator-v0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "transformers", | |
| "backend_ready": true, | |
| "dependency_status": { | |
| "mlx": false, | |
| "mlx_lm": false, | |
| "torch": true, | |
| "transformers": true | |
| }, | |
| "machine": "arm64", | |
| "platform": "macOS-26.3-arm64-arm-64bit", | |
| "python_supported_for_torch": true, | |
| "python_version": "3.11.14", | |
| "ready_for_local_head_training": true, | |
| "reasons": [], | |
| "recommendations": [ | |
| "run a frozen-backbone head-training smoke before enabling LoRA or backbone updates" | |
| ], | |
| "require_gpu": false, | |
| "schema_version": "mempool.qwen_training_readiness.v1" | |
| } | |