Create README.md

README.md

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+---
+language:
+- en
+---
+
+
+This model was trained with [Sparsembed](https://github.com/raphaelsty/sparsembed). You can find details on how to use it in the [Sparsembed](https://github.com/raphaelsty/sparsembed) repository.
+
+```sh
+pip install sparsembed
+```
+
+```python
+from sparsembed import model, retrieve
+from transformers import AutoModelForMaskedLM, AutoTokenizer
+
+device = "cuda" # cpu
+
+batch_size = 10
+
+# List documents to index:
+documents = [
+ {'id': 0,
+  'title': 'Paris',
+  'url': 'https://en.wikipedia.org/wiki/Paris',
+  'text': 'Paris is the capital and most populous city of France.'},
+ {'id': 1,
+  'title': 'Paris',
+  'url': 'https://en.wikipedia.org/wiki/Paris',
+  'text': "Since the 17th century, Paris has been one of Europe's major centres of science, and arts."},
+ {'id': 2,
+  'title': 'Paris',
+  'url': 'https://en.wikipedia.org/wiki/Paris',
+  'text': 'The City of Paris is the centre and seat of government of the region and province of Île-de-France.'
+}]
+
+model = model.Splade(
+    model=AutoModelForMaskedLM.from_pretrained("raphaelsty/splade_max").to(device),
+    tokenizer=AutoTokenizer.from_pretrained("raphaelsty/splade_max"),
+    device=device
+)
+
+retriever = retrieve.SpladeRetriever(
+    key="id", # Key identifier of each document.
+    on=["title", "text"], # Fields to search.
+    model=model # Splade retriever.
+)
+
+retriever = retriever.add(
+    documents=documents,
+    batch_size=batch_size,
+    k_tokens=256, # Number of activated tokens.
+)
+
+retriever(
+    ["paris", "Toulouse"], # Queries 
+    k_tokens=20, # Maximum number of activated tokens.
+    k=100, # Number of documents to retrieve.
+    batch_size=batch_size
+)
+```