Instructions to use Salesforce/SFR-Embedding-Mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Salesforce/SFR-Embedding-Mistral with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Salesforce/SFR-Embedding-Mistral") 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 Salesforce/SFR-Embedding-Mistral with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Salesforce/SFR-Embedding-Mistral")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Salesforce/SFR-Embedding-Mistral") model = AutoModelForMultimodalLM.from_pretrained("Salesforce/SFR-Embedding-Mistral") - Notebooks
- Google Colab
- Kaggle
No sentence-transformers model found with name Salesforce/SFR-Embedding-Mistral. Creating a new one with MEAN pooling.
import os
os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com'
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Salesforce/SFR-Embedding-Mistral", cache_folder="/root/autodl-tmp/model/SFR")
No sentence-transformers model found with name Salesforce/SFR-Embedding-Mistral. Creating a new one with MEAN pooling.
Traceback (most recent call last):
File "", line 1, in
File "/root/miniconda3/envs/llmesr_4090/lib/python3.9/site-packages/sentence_transformers/SentenceTransformer.py", line 97, in init
modules = self._load_auto_model(model_path)
File "/root/miniconda3/envs/llmesr_4090/lib/python3.9/site-packages/sentence_transformers/SentenceTransformer.py", line 806, in _load_auto_model
transformer_model = Transformer(model_name_or_path)
File "/root/miniconda3/envs/llmesr_4090/lib/python3.9/site-packages/sentence_transformers/models/Transformer.py", line 28, in init
config = AutoConfig.from_pretrained(model_name_or_path, **model_args, cache_dir=cache_dir)
File "/root/miniconda3/envs/llmesr_4090/lib/python3.9/site-packages/transformers/models/auto/configuration_auto.py", line 916, in from_pretrained
config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
File "/root/miniconda3/envs/llmesr_4090/lib/python3.9/site-packages/transformers/configuration_utils.py", line 573, in get_config_dict
config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
File "/root/miniconda3/envs/llmesr_4090/lib/python3.9/site-packages/transformers/configuration_utils.py", line 628, in _get_config_dict
resolved_config_file = cached_file(
File "/root/miniconda3/envs/llmesr_4090/lib/python3.9/site-packages/transformers/utils/hub.py", line 380, in cached_file
raise EnvironmentError(
OSError: Salesforce/SFR-Embedding-Mistral does not appear to have a file named config.json. Checkout 'https://huggingface.co/Salesforce/SFR-Embedding-Mistral/None' for available files.