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: 1,964 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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | {
"args": {
"task_file": "scripts/fallacies.json",
"dataset": null,
"dataset_revision": null,
"split": "train",
"text_column": null,
"label_column": null,
"model_dir": null,
"base_revision": "1c5edc17a7acd8701df6fc341c0d179f1c62c982",
"output_dir": "./tmp/stage1",
"device": "auto",
"amp": false,
"epochs": 4,
"micro_batch": 8,
"grad_accum": 4,
"group_size": 4,
"lr_encoder": 2.5e-05,
"lr_head": 0.0001,
"weight_decay": 0.01,
"sigma_start": 0.4,
"sigma_end": 0.1,
"seed": 42,
"max_items": 0,
"calib_max": 400,
"val_frac": 0.1,
"negative_file": "/Users/brian/git/receptron/laya/scripts/negatives.jsonl",
"extra_file": "none",
"dry_run": false,
"dry_steps": 5,
"finalize_only": false
},
"base_model": "convaiinnovations/laya",
"base_revision": "1c5edc17a7acd8701df6fc341c0d179f1c62c982",
"base_model_dir": "/Users/brian/.cache/huggingface/hub/models--convaiinnovations--laya/snapshots/1c5edc17a7acd8701df6fc341c0d179f1c62c982",
"dataset": "tasksource/logical-fallacy",
"dataset_revision": "37e9b0537a86e72e9eaf6ee8c9a27d872a944103",
"env": {
"laya": "0.3.5",
"torch": "2.14.0",
"transformers": "5.17.0",
"datasets": "5.0.1",
"safetensors": "0.8.0",
"numpy": "2.5.3"
},
"epochs": [
{
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},
{
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{
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{
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}
],
"fitted_temperatures": [
1.8769,
1.2,
1.2
],
"val": {
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"n": 243
},
"test": {
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"mean_argmax_confidence": 0.6494024801860817,
"n": 511
},
"train_items": 2196,
"device": "mps",
"amp": false
} |