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: 655 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 24 | {
"id": "decosa-cell-pointer",
"version": "cell-pointer.v1",
"base": "answerdotai/ModernBERT-base",
"view": "blind",
"max_len": 2048,
"ops": [
"none",
"diff",
"sum",
"pct",
"ratio",
"reduction"
],
"temperature": 1.4,
"cascade_threshold": 0.6,
"pad_id": 50283,
"licence": "Apache-2.0",
"onnx_sha256": "141e67c37ffca905f972f6b6db13e950f0a1eca455a0fe67bf7635eb1b7266c9",
"heads_sha256": "a2d6428ffb7d6c44f08a7113ac12f7d9453298300a8125f616fde6d571a69d2a",
"safetensors_sha256": "69428a7a3f5f6402b44c7b08bac1b49d471fa2e27035f56727a20b0f5f4fff13",
"model_version": "v2-blind",
"repo": "decosaai/decosa-cell-pointer-modernbert-base"
} |