Text Classification
Laya
Safetensors
English
voice-agents
turn-taking
barge-in
intent-classification
calibration
Instructions to use enz23/floorcall with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use enz23/floorcall 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 rl_agent_config.json from enz23/floorcall: direct link, hf CLI and curl.
- Browser
- Download file 2.19 kB
-
https://huggingface.co/enz23/floorcall/resolve/main/rl_agent_config.json
- Command line
-
hf download hf://enz23/floorcall/rl_agent_config.json
-
curl -L -o rl_agent_config.json https://huggingface.co/enz23/floorcall/resolve/main/rl_agent_config.json
2.19 kB
| { | |
| "encoder": "answerdotai/ModernBERT-large", | |
| "head_layers": 2, | |
| "max_len": 512, | |
| "head_max_len": 192, | |
| "max_prefixes": 6, | |
| "act_costs": { | |
| "escalate": 0.5 | |
| }, | |
| "cost_wrong_act": 3.0, | |
| "amp_dtype": "bf16", | |
| "model_name": "floorcall", | |
| "temperature": [ | |
| 1.0, | |
| 1.0, | |
| 1.0 | |
| ], | |
| "training": { | |
| "updates": 7313, | |
| "epochs_completed": 1, | |
| "hours": 1.96, | |
| "world_size": 1, | |
| "fine_tuned_from_checkpoint": true | |
| }, | |
| "fine_tuned": true, | |
| "floorcall": { | |
| "code": "00fac02", | |
| "base_checkpoint": "convaiinnovations/laya", | |
| "base_revision": "55cf4c4ebb4ebe31b2550e8bdf3bd21b99753851", | |
| "tasks": [ | |
| "turn_complete", | |
| "barge_in", | |
| "route", | |
| "escalate" | |
| ], | |
| "train_sha256": { | |
| "turn_complete": "c2477590bb773aca53089d7435100f59461ddbf3a5934819c4dfb6faec3e92fa", | |
| "barge_in": "d065fb36b9c1b2f4231dc17d4343e0c99cce5bc5b4ed41a4d6d7780213e57cd6", | |
| "route": "348491cc1518f0807e871079121c6dbf60b3abb0035a34965674e5d4b30547e0", | |
| "escalate": "61bc010a9534ebab16a954c933fe0231e3b07f457a6a8f3876cb5ba12e349bb0" | |
| }, | |
| "test_manifest": { | |
| "barge_in.test.v1.jsonl.gz": "c3b1461f0b625ad7cdf33732746786011a7f3e39a8d1798975875a2235716f14", | |
| "escalate.test.v1.jsonl.gz": "e69e48237ad70244c17eb336e0114a38166ad16c0c2bfd5e9dc172276b458d48", | |
| "escalate.test.v2.jsonl.gz": "91994160a288950ef3a820df09359149c65bcb636b146dedc41a9d5a6c1ece97", | |
| "route.test.v1.jsonl.gz": "9d1850a88cf6411c4b54e8e04bc596905f7379e29b5383620bcd41618e021607", | |
| "turn_complete.test.v1.jsonl.gz": "61535c7876b307c20001be578eb692dfb9d43d7e7c5e59c1a7f2cc6108ff7f3c" | |
| }, | |
| "dev": { | |
| "fraction": 0.05, | |
| "rows": { | |
| "turn_complete": 2717, | |
| "barge_in": 2693, | |
| "route": 88, | |
| "escalate": 300 | |
| }, | |
| "rule": "conversations held out of each task's train rows, seeded; the kept checkpoint is the epoch with the lowest dev cross-entropy at T = 1, averaged over tasks" | |
| }, | |
| "epoch": 2, | |
| "dev_ce_by_task": { | |
| "barge_in": 0.07300145255392738, | |
| "escalate": 0.2805749692519506, | |
| "route": 0.08430903302558529, | |
| "turn_complete": 0.37864744114796817 | |
| } | |
| } | |
| } | |