Feature Extraction
Transformers
Safetensors
PyTorch
Chinese
English
dreammachine
recommendation
retrieval
dual-tower
transformer
multi-hash-embedding
Dream-Machine-08-09
custom_code
Eval Results (legacy)
Instructions to use dream-machine-ai/Dream-Machine-08-09 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dream-machine-ai/Dream-Machine-08-09 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dream-machine-ai/Dream-Machine-08-09", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dream-machine-ai/Dream-Machine-08-09", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| """ | |
| DreamMachine HuggingFace Model Package | |
| Copyright (c) 2026 Fangjun Wen / DreamMachine Research Team | |
| Registers DreamMachine with HuggingFace AutoClasses so that: | |
| AutoConfig.from_pretrained("fangjunwen/dreammachine", trust_remote_code=True) | |
| AutoModel.from_pretrained("fangjunwen/dreammachine", trust_remote_code=True) | |
| AutoTokenizer.from_pretrained("...", trust_remote_code=True) | |
| AutoFeatureExtractor.from_pretrained("...", trust_remote_code=True) | |
| all work out of the box. | |
| """ | |
| from configuration_dreammachine import DreamMachineConfig | |
| from modeling_dreammachine import DreamMachineModel, DreamMachineOutput | |
| from tokenization_dreammachine import DreamMachineTokenizer | |
| from feature_extraction_dreammachine import DreamMachineFeatureExtractor | |
| try: | |
| from transformers import ( | |
| AutoConfig, AutoModel, AutoTokenizer, AutoFeatureExtractor, | |
| AutoModelForSequenceClassification, | |
| ) | |
| AutoConfig.register("dreammachine", DreamMachineConfig) | |
| AutoModel.register(DreamMachineConfig, DreamMachineModel) | |
| AutoModelForSequenceClassification.register(DreamMachineConfig, DreamMachineModel) | |
| AutoTokenizer.register(DreamMachineConfig, slow_tokenizer_class=DreamMachineTokenizer) | |
| AutoFeatureExtractor.register(DreamMachineConfig, DreamMachineFeatureExtractor) | |
| except Exception: | |
| pass | |
| __version__ = "1.0.0" | |
| __all__ = [ | |
| "DreamMachineConfig", | |
| "DreamMachineModel", | |
| "DreamMachineOutput", | |
| "DreamMachineTokenizer", | |
| "DreamMachineFeatureExtractor", | |
| ] | |