Echo-DSRN - Classifier
Collection
9 items • Updated
How to use ethicalabs/Echo-DSRN-v0.1.3-Research-Intent-CLF with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="ethicalabs/Echo-DSRN-v0.1.3-Research-Intent-CLF", trust_remote_code=True) # Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("ethicalabs/Echo-DSRN-v0.1.3-Research-Intent-CLF", trust_remote_code=True, dtype="auto")This repository contains experimental models designed strictly for academic evaluation and research purposes.
Critical Constraints:
- No Production Deployment: Experimental models must not be deployed in commercial, enterprise, or mission-critical environments under any circumstances.
- No Liability: Experimental models are provided "as-is" without warranties of any kind. The developers assume zero liability for downstream consequences, system integration failures, or regulatory non-compliance resulting from unauthorized deployment.
This is a 98 million parameters sequence classification model based on the Echo-DSRN architecture, trained on a single AMD GPU using ROCm 7.2.
It is based on ethicalabs/Echo-DSRN-114M-v0.1.2.
Coming Soon!
Base model
ethicalabs/Echo-DSRN-114M-v0.1.2-Base