chore: update README

README.md

@@ -40,7 +40,7 @@ language:
 ## Usage
 
 <details>
-<summary>Via API (Standard Embeddings)</summary>
+<summary>Via API</summary>
 
 ```bash
 curl -X POST https://api.perplexity.ai/v1/embeddings \
@@ -60,73 +60,6 @@ curl -X POST https://api.perplexity.ai/v1/embeddings \
 
 </details>
 
-<details>
-<summary>Via API (Contextualized Embeddings)</summary>
-
-```bash
-curl -X POST https://api.perplexity.ai/v1/contextualizedembeddings \
-  -H "Authorization: Bearer YOUR_API_KEY" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "inputs": [
-      [
-        "Curiosity begins in childhood with endless questions about the world.",
-        "As we grow, curiosity drives us to explore new ideas and challenge assumptions.",
-        "Scientific breakthroughs often start with a simple curious question."
-      ],
-      [
-        "The curiosity rover explores Mars, searching for signs of ancient life.",
-        "Each discovery on Mars sparks new questions about our place in the universe."
-      ]
-    ],
-    "model": "pplx-embed-1-context-4B"
-  }'
-```
-
-</details>
-
-<details>
-<summary>Using Transformers</summary>
-
-```python
-from transformers import AutoModel
-
-model = AutoModel.from_pretrained(
-    "perplexity-ai/pplx-embed-1-0.6B",
-    trust_remote_code=True
-)
-texts = [
-    "Scientists explore the universe driven by curiosity.",
-    "Children learn through curious exploration.",
-    "Historical discoveries began with curious questions.",
-    "Animals use curiosity to adapt and survive.",
-    "Philosophy examines the nature of curiosity.",
-]
-
-embeddings = model.encode(texts) # Shape: (5, 1024)
-
-model_ctx = AutoModel.from_pretrained(
-    "perplexity-ai/pplx-embed-1-context-0.6B",
-    trust_remote_code=True
-)
-
-doc_chunks = [
-    [
-        "Curiosity begins in childhood with endless questions about the world.",
-        "As we grow, curiosity drives us to explore new ideas.",
-        "Scientific breakthroughs often start with a curious question."
-    ],
-    [
-        "The curiosity rover explores Mars searching for ancient life.",
-        "Each discovery on Mars sparks new questions about the universe."
-    ]
-]
-# Returns list of numpy arrays (one per document)
-# embeddings[0].shape = (3, 1024), embeddings[1].shape = (2, 1024)
-embeddings = model_ctx.encode(doc_chunks)
-```
-
-</details>
 
 <details>
 <summary>Using SentenceTransformers</summary>
@@ -135,7 +68,7 @@ embeddings = model_ctx.encode(doc_chunks)
 from sentence_transformers import SentenceTransformer
 
 model = SentenceTransformer(
-    "perplexity-ai/pplx-embed-1-0.6B",
+    "perplexity-ai/pplx-embed-1-4B",
     trust_remote_code=True
 )
 
@@ -147,32 +80,12 @@ texts = [
     "Philosophy examines the nature of curiosity.",
 ]
 
-embeddings = model.encode(texts) # Shape: (5, 1024)
-
-model_ctx = SentenceTransformer(
-    "perplexity-ai/pplx-embed-1-context-0.6B",
-    trust_remote_code=True
-)
-
-doc_chunks = [
-    [
-        "Curiosity begins in childhood with endless questions about the world.",
-        "As we grow, curiosity drives us to explore new ideas.",
-        "Scientific breakthroughs often start with a curious question."
-    ],
-    [
-        "The curiosity rover explores Mars searching for ancient life.",
-        "Each discovery on Mars sparks new questions about the universe."
-    ]
-]
-# Returns list of numpy arrays (one per document)
-# embeddings[0].shape = (3, 1024), embeddings[1].shape = (2, 1024)
-embeddings = model_ctx.encode(doc_chunks)
+embeddings = model.encode(texts) # Shape: (5, 2560), quantized to int8
+embeddings = model.encode(texts, quantization="binary") # Shape: (5, 2560), quantized to binary
 ```
 
 </details>
 
-</details>
 
 ## Technical Details