Feature Extraction
sentence-transformers
PyTorch
Safetensors
Transformers
English
mistral
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use Alignment-Lab-AI/e5-mistral-7b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Alignment-Lab-AI/e5-mistral-7b-instruct with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Alignment-Lab-AI/e5-mistral-7b-instruct") 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] - Transformers
How to use Alignment-Lab-AI/e5-mistral-7b-instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Alignment-Lab-AI/e5-mistral-7b-instruct")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Alignment-Lab-AI/e5-mistral-7b-instruct") model = AutoModel.from_pretrained("Alignment-Lab-AI/e5-mistral-7b-instruct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
69b92ca | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:143df9048bac75b444ff6faba463220a7d109630ffdffd8bc90ac6f3ba5ddc0a
size 4278390829
|