Text Classification
Transformers
Safetensors
Laya
English
system-one
calibrated-decisions
logical-fallacy
debate
modernbert
Instructions to use BryanSnappCTO/laya-fallacies with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BryanSnappCTO/laya-fallacies with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BryanSnappCTO/laya-fallacies")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BryanSnappCTO/laya-fallacies", device_map="auto") - Laya
How to use BryanSnappCTO/laya-fallacies 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
File size: 554 Bytes
356ec59 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"encoder": "answerdotai/ModernBERT-large",
"head_layers": 2,
"max_len": 1024,
"head_max_len": 256,
"max_prefixes": 6,
"act_costs": {
"escalate": 0.5
},
"cost_wrong_act": 3.0,
"amp_dtype": "bf16",
"model_name": "laya-fallacies",
"temperature": [
1.876949429512024,
1.2,
1.2
],
"training": {
"updates": 7313,
"epochs_completed": 1,
"hours": 1.96,
"world_size": 1,
"fine_tuned_from_checkpoint": true
},
"gradient_checkpointing": true,
"max_tokens_per_batch": 4096,
"fine_tuned": true
} |