YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/model-cards#model-card-metadata)
bert_assurance
Model Description
This is the model card of an insurance embeddings model that has been trained on customer documentation with 50K datapoints.
- Developed by: Taymed
- Model type: BERT base finetuned
- Language(s) (NLP): Fr
- License: [Spellz ltd]
- Finetuned from model: [BERT base]
Model Sources [optional]
- Huggingface: [https://huggingface.co/google-bert/bert-base-uncased]
How to Get Started with the Model
from transformers import AutoTokenizer, AutoModel
import torch
# Define the model name (either your custom model or a pre-trained model from Hugging Face)
model_name = "ortaymed/bert_assurance" # Replace with your model name or path
# Your Hugging Face token
hf_token = "your-huggingface-token" # Replace with your actual Hugging Face token
# Load the tokenizer and model with the token
tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=hf_token)
model = AutoModel.from_pretrained(model_name, use_auth_token=hf_token)
# Sample input text
input_text = "Your sample input text goes here."
# Tokenize the input text
inputs = tokenizer(input_text, return_tensors="pt")
# Get embeddings
with torch.no_grad():
outputs = model(**inputs)
# Get the embeddings from the last hidden state
embeddings = outputs.last_hidden_state
print(embeddings)
- Downloads last month
- 7
Inference API (serverless) is not available, repository is disabled.