esg-x/esg-embedding-model

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Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

• Developed by: [More Information Needed]
• Model type: [More Information Needed]
• Language(s) (NLP): [More Information Needed]
• License: [More Information Needed]
• Finetuned from model [optional]: sentence-transformers/all-MiniLM-L6-v2

Model Sources [optional]

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• Paper [optional]: [More Information Needed]
• Demo [optional]: [More Information Needed]

Uses

Direct Use

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Downstream Use [optional]

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

from transformers import AutoModel, AutoTokenizer
model_name = "sentence-transformers/all-MiniLM-L6-v2"

# Load the tokenizer, model and adapter
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModel.from_pretrained(model_name)
model.load_adapter("esg-x/esg-embedding-model")

text = "I love ESG"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)

Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Glossary [optional]

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