Transformers
Safetensors
Laya
system-one
calibrated-decisions
rlcd
structured-decisions
typed-decisions
benchmark
glendesk
call-analysis
Eval Results (legacy)
Instructions to use fcelabs/laya-glendesk-issues with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fcelabs/laya-glendesk-issues with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fcelabs/laya-glendesk-issues", device_map="auto") - Laya
How to use fcelabs/laya-glendesk-issues 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 fcelabs/laya-glendesk-issues: direct link, hf CLI and curl.
- Browser
- Download file 546 Bytes
-
https://huggingface.co/fcelabs/laya-glendesk-issues/resolve/main/rl_agent_config.json
- Command line
-
hf download hf://fcelabs/laya-glendesk-issues/rl_agent_config.json
-
curl -L -o rl_agent_config.json https://huggingface.co/fcelabs/laya-glendesk-issues/resolve/main/rl_agent_config.json
546 Bytes
| { | |
| "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-typed-decisions", | |
| "temperature": [ | |
| 1.2, | |
| 1.2, | |
| 1.0 | |
| ], | |
| "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 | |
| } |