Shenzy/Sentence_Classification4DesignTutor

1---2tags: autotrain3language: en4widget:5- text: "An unusual hierarchy in the section near the top where the design seems to prioritise running time over a compacted artist name."6datasets:7- Shenzy/autotrain-data-sentence_classification8co2_eq_emissions: 0.009864943870434999---10 11## Validation Metrics12 13- Loss: 0.644772648811340314- Accuracy: 0.826347305389221515- Macro F1: 0.777655505539203616- Micro F1: 0.826347305389221517- Weighted F1: 0.816151159197378818- Macro Precision: 0.827350427350427419- Micro Precision: 0.826347305389221520- Weighted Precision: 0.826669737448180621- Macro Recall: 0.761551874455100322- Micro Recall: 0.826347305389221523- Weighted Recall: 0.826347305389221524 25 26## Usage27 28You can use cURL to access this model:29 30```31$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "An unusual hierarchy in the section near the top where the design seems to prioritise running time over a compacted artist name."}' https://api-inference.huggingface.co/models/Shenzy/Sentence_Classification4DesignTutor32```33 34Or Python API:35 36```37from transformers import AutoModelForSequenceClassification, AutoTokenizer38 39import numpy as np40 41labdic ={ 0: "rationale", 1: "suggestion", 2: "specific_critique"}42 43model = AutoModelForSequenceClassification.from_pretrained("Shenzy/Sentence_Classification4DesignTutor")44 45tokenizer = AutoTokenizer.from_pretrained("Shenzy/Sentence_Classification4DesignTutor")46 47inputs = tokenizer("An unusual hierarchy in the section near the top where the design seems to prioritise running time over a compacted artist name.", return_tensors="pt")48 49outputs = model(**inputs)50 51print(labdic[np.argmax(outputs)])52```