# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Erin/mist-zh")
model = AutoModel.from_pretrained("Erin/mist-zh")Quick Links
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Evaluation results
- cos_sim_pearson on MTEB AFQMCvalidation set self-reported44.809
- cos_sim_spearman on MTEB AFQMCvalidation set self-reported46.979
- euclidean_pearson on MTEB AFQMCvalidation set self-reported45.368
- euclidean_spearman on MTEB AFQMCvalidation set self-reported46.979
- manhattan_pearson on MTEB AFQMCvalidation set self-reported45.235
- manhattan_spearman on MTEB AFQMCvalidation set self-reported46.877
- cos_sim_pearson on MTEB ATECtest set self-reported49.529
- cos_sim_spearman on MTEB ATECtest set self-reported51.348
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Erin/mist-zh")