How to use danielruss/is_job_title_gist_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielruss/is_job_title_gist_small")
# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielruss/is_job_title_gist_small") model = AutoModelForSequenceClassification.from_pretrained("danielruss/is_job_title_gist_small", device_map="auto")
How to use danielruss/is_job_title_gist_small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danielruss/is_job_title_gist_small") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]
How to use danielruss/is_job_title_gist_small with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'danielruss/is_job_title_gist_small');
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