Table Question Answering
Transformers
ONNX
Safetensors
English
modernbert
fill-mask
table-grounding
number-verification
clinical-study-report
Instructions to use decosaai/decosa-cell-pointer-modernbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use decosaai/decosa-cell-pointer-modernbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="decosaai/decosa-cell-pointer-modernbert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("decosaai/decosa-cell-pointer-modernbert-base") model = AutoModelForMaskedLM.from_pretrained("decosaai/decosa-cell-pointer-modernbert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 643 Bytes
2769c0b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"id": "decosa-cell-pointer-aware",
"version": "cell-pointer.v1",
"base": "answerdotai/ModernBERT-base",
"view": "aware",
"max_len": 2048,
"ops": [
"none",
"diff",
"sum",
"pct",
"ratio",
"reduction"
],
"temperature": 1.4,
"pad_id": 50283,
"licence": "Apache-2.0",
"onnx_sha256": "cd0617df4e21c5beeeaf1a775e9e553e995a35812c9976cefb0e052b119743ab",
"heads_sha256": "27724866e9568de2948012b21217db6062b17d62f36b3af66f5ab3a0df6c13e1",
"safetensors_sha256": "d6b3ec8d22ee0c261a18dcf928ddd250ffb68821eaac79a83d4efb94c03824c1",
"model_version": "v1-aware",
"repo": "decosaai/decosa-cell-pointer-modernbert-base (aware/)"
} |