Feature Extraction
Transformers
PyTorch
Safetensors
English
hastejev
jev
decision-engine
system-1
agent-routing
tool-routing
non-generative
pica
quantized
Instructions to use noffy/hastejev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noffy/hastejev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="noffy/hastejev")# Load model directly from transformers import HasteJevEngine model = HasteJevEngine.from_pretrained("noffy/hastejev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from noffy/hastejev: direct link, hf CLI and curl.
- Browser
- Download file 357 Bytes
-
https://huggingface.co/noffy/hastejev/resolve/72fc70920e882de645b46dd9f63ad09a9831cc74/config.json
- Command line
-
hf download hf://noffy/hastejev@72fc70920e882de645b46dd9f63ad09a9831cc74/config.json
-
curl -L -o config.json https://huggingface.co/noffy/hastejev/resolve/72fc70920e882de645b46dd9f63ad09a9831cc74/config.json
357 Bytes
| { | |
| "architectures": [ | |
| "HasteJevEngine" | |
| ], | |
| "model_type": "hastejev", | |
| "preset_name": "20m", | |
| "d_model": 256, | |
| "n_layers": 4, | |
| "n_heads": 4, | |
| "d_ff": 1024, | |
| "table_size": 65536, | |
| "num_frequencies": 32, | |
| "vocab_size": 30522, | |
| "calibrator_temperature": 1.0, | |
| "torch_dtype": "float32", | |
| "quantization": "int4", | |
| "hastejev_version": "1.1.0" | |
| } |