Text Classification
Transformers
Safetensors
Laya
system-one
calibrated-decisions
rlcd
classification
routing
scoring
guardrails
moderation
reinforcement-learning
commercial-use
Instructions to use dev-amarnadh-gandham/laya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dev-amarnadh-gandham/laya with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dev-amarnadh-gandham/laya")# pip install -U transformers accelerate # Load model directly from transformers import LayaTypedDecisions model = LayaTypedDecisions.from_pretrained("dev-amarnadh-gandham/laya", device_map="auto") - Laya
How to use dev-amarnadh-gandham/laya with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Download config.json from dev-amarnadh-gandham/laya: direct link, hf CLI and curl.
- Browser
- Download file 160 Bytes
-
https://huggingface.co/dev-amarnadh-gandham/laya/resolve/main/config.json
- Command line
-
hf download hf://dev-amarnadh-gandham/laya/config.json
-
curl -L -o config.json https://huggingface.co/dev-amarnadh-gandham/laya/resolve/main/config.json
160 Bytes
| { | |
| "model_type": "laya", | |
| "architectures": [ | |
| "LayaTypedDecisions" | |
| ], | |
| "_comment": "Root config for Hub download tracking. See README for how to load Laya." | |
| } |