Salesforce

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SFR-Embedding-Mistral

like 230

Excited for this to merge! Wondering what the ETA is on this PR? Also could you please enable the ability to get the raw embedding in addition to the cosine similarity scores?

Thanks!

cc: @memray @yliu279 @yeliu918

I'd like to ask you to have a look at this PR!
Anyone can already use this model like so:

from sentence_transformers import SentenceTransformer, util

model = SentenceTransformer("Salesforce/SFR-Embedding-Mistral", revision="refs/pr/1")

def get_detailed_instruct(task_description: str, query: str) -> str:
    return f'Instruct: {task_description}\nQuery: {query}'

# Each query must come with a one-sentence instruction that describes the task
task = 'Given a web search query, retrieve relevant passages that answer the query'
queries = [
    get_detailed_instruct(task, 'How to bake a chocolate cake'),
    get_detailed_instruct(task, 'Symptoms of the flu')
]
# No need to add instruction for retrieval documents
passages = [
    "To bake a delicious chocolate cake, you'll need the following ingredients: all-purpose flour, sugar, cocoa powder, baking powder, baking soda, salt, eggs, milk, vegetable oil, and vanilla extract. Start by preheating your oven to 350°F (175°C). In a mixing bowl, combine the dry ingredients (flour, sugar, cocoa powder, baking powder, baking soda, and salt). In a separate bowl, whisk together the wet ingredients (eggs, milk, vegetable oil, and vanilla extract). Gradually add the wet mixture to the dry ingredients, stirring until well combined. Pour the batter into a greased cake pan and bake for 30-35 minutes. Let it cool before frosting with your favorite chocolate frosting. Enjoy your homemade chocolate cake!",
    "The flu, or influenza, is an illness caused by influenza viruses. Common symptoms of the flu include a high fever, chills, cough, sore throat, runny or stuffy nose, body aches, headache, fatigue, and sometimes nausea and vomiting. These symptoms can come on suddenly and are usually more severe than the common cold. It's important to get plenty of rest, stay hydrated, and consult a healthcare professional if you suspect you have the flu. In some cases, antiviral medications can help alleviate symptoms and reduce the duration of the illness."
]

embeddings = model.encode(queries + passages)
scores = util.cos_sim(embeddings[:2], embeddings[2:]) * 100
print(scores.tolist())
# [[86.71537780761719, 36.645721435546875], [35.00497055053711, 82.07388305664062]]

After merging, users won't have to include revision="refs/pr/1" anymore.

• Tom Aarsen

@tomaarsen

Thanks for the above response! Yes, I have been using this code on a local GPU for the last few weeks and it works great!

I just want to be able to deploy this on a HuggingFace Inference Endpoint for easy deployment and management (like with gtr-t5-xxl and all-mpnet-base-v2). It's nice to have a lot of the deployment steps abstracted away. Thanks again!