Feature Extraction
sentence-transformers
PyTorch
Safetensors
Transformers
English
mistral
mteb
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use intfloat/e5-mistral-7b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-mistral-7b-instruct with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/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 intfloat/e5-mistral-7b-instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="intfloat/e5-mistral-7b-instruct")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("intfloat/e5-mistral-7b-instruct") model = AutoModel.from_pretrained("intfloat/e5-mistral-7b-instruct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Simplify usage; integrate Sentence Transformers (+ LlamaIndex/LangChain, etc.) (#39)
Verified signature- Add "add_eos_token" to tokenizer config; simplify usage (a5e1612ae784f73eba634b00acf64db7d99ad7e9) - Integrate with Sentence Transformers + 3rd parties (90cddb89718db232ed6257f69b36e9e601120883) - Reduce sentence-transformers version to prevent "Upgrade your ST" warning (84b20972705a9d8c825bdf39a81acac66a10d701)07163b7