Transformers
Safetensors
Laya
enterprise-reflex
enterprise-reflux-laya
system-one
rlcd
dynamic-actions
calibrated-decisions
Instructions to use yasserrmd/enterprise-reflux-laya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yasserrmd/enterprise-reflux-laya with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yasserrmd/enterprise-reflux-laya", device_map="auto") - Laya
How to use yasserrmd/enterprise-reflux-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
File size: 777 Bytes
60bfe69 | 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 | {
"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": "enterprise-reflux-laya",
"temperature": [
3.50919508934021,
1.0,
1.0
],
"temperature_by_options": {},
"training": {
"recipe": "Laya RLCD + soft CE",
"base_model": "convaiinnovations/laya",
"epochs": 4,
"updates": 3696,
"encoder_lr": 2.5e-05,
"head_lr": 0.0001,
"group_size": 4,
"sigma_start": 0.4,
"sigma_end": 0.1,
"v1_train_repeat": 2,
"calibration_held_out_before_training": true
},
"gradient_checkpointing": true,
"max_tokens_per_batch": 4096,
"fine_tuned": true
} |