Text Classification
Transformers
Safetensors
laya
system-one
calibrated-decisions
rlcd
classification
routing
scoring
guardrails
moderation
reinforcement-learning
commercial-use
Instructions to use convaiinnovations/laya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use convaiinnovations/laya with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="convaiinnovations/laya")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("convaiinnovations/laya", device_map="auto") - Notebooks
- Google Colab
- Kaggle
assets: host benchmark figures in the repo
Browse files- .gitattributes +1 -0
- assets/laya_benchmark_common.png +3 -0
.gitattributes
CHANGED
|
@@ -37,3 +37,4 @@ eval/benchmark_comparison.png filter=lfs diff=lfs merge=lfs -text
|
|
| 37 |
multilingual/tokenizer/tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
| 38 |
assets/laya_vs_jev.png filter=lfs diff=lfs merge=lfs -text
|
| 39 |
assets/laya_benchmark.png filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 37 |
multilingual/tokenizer/tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
| 38 |
assets/laya_vs_jev.png filter=lfs diff=lfs merge=lfs -text
|
| 39 |
assets/laya_benchmark.png filter=lfs diff=lfs merge=lfs -text
|
| 40 |
+
assets/laya_benchmark_common.png filter=lfs diff=lfs merge=lfs -text
|
assets/laya_benchmark_common.png
ADDED
|
Git LFS Details
|