Feature Extraction
sentence-transformers
ONNX
Safetensors
Laya
Transformers.js
bert
verdict
decision-model
system-one
jev
classification
calibration
Eval Results (legacy)
text-embeddings-inference
Instructions to use Manav2op/verdict-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Manav2op/verdict-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Manav2op/verdict-small") sentences = [ "query: Hi, we were billed twice for March. Please refund the duplicate today.", "passage: What does the user want? invoices, payments, refunds", "passage: What does the user want? bugs, outages, errors", "passage: What does the user want? pricing, new contracts" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Laya
How to use Manav2op/verdict-small 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
- Transformers.js
How to use Manav2op/verdict-small with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'Manav2op/verdict-small'); - Notebooks
- Google Colab
- Kaggle
Download modules.json from Manav2op/verdict-small: direct link, hf CLI and curl.
- Browser
- Download file 413 Bytes
-
https://huggingface.co/Manav2op/verdict-small/resolve/main/modules.json
- Command line
-
hf download hf://Manav2op/verdict-small/modules.json
-
curl -L -o modules.json https://huggingface.co/Manav2op/verdict-small/resolve/main/modules.json
413 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.base.modules.transformer.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.sentence_transformer.modules.pooling.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.base.modules.normalize.Normalize" | |
| } | |
| ] |