docs: fix the code snippets
Browse files
README.md
CHANGED
@@ -238,26 +238,32 @@ model = SentenceTransformer("jinaai/jina-embeddings-v4", trust_remote_code=True)
|
|
238 |
# 1. Retrieval Task
|
239 |
# ========================
|
240 |
# Encode query
|
241 |
-
|
242 |
sentences=["Overview of climate change impacts on coastal cities"],
|
243 |
task="retrieval",
|
244 |
prompt_name="query",
|
245 |
-
)
|
|
|
|
|
246 |
|
247 |
# Encode passage (text)
|
248 |
-
|
249 |
sentences=[
|
250 |
"Climate change has led to rising sea levels, increased frequency of extreme weather events..."
|
251 |
],
|
252 |
task="retrieval",
|
253 |
prompt_name="passage",
|
254 |
-
)
|
|
|
|
|
255 |
|
256 |
# Encode image/document
|
257 |
-
|
258 |
sentences=["https://i.ibb.co/nQNGqL0/beach1.jpg"],
|
259 |
task="retrieval",
|
260 |
-
)
|
|
|
|
|
261 |
|
262 |
# ========================
|
263 |
# 2. Text Matching Task
|
@@ -281,7 +287,7 @@ text_embeddings = model.encode(sentences=texts, task="text-matching")
|
|
281 |
# ========================
|
282 |
|
283 |
# Encode query
|
284 |
-
|
285 |
sentences=["Find a function that prints a greeting message to the console"],
|
286 |
task="code",
|
287 |
prompt_name="query",
|
@@ -293,6 +299,25 @@ code_embeddings = model.encode(
|
|
293 |
task="code",
|
294 |
prompt_name="passage",
|
295 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
296 |
```
|
297 |
</details>
|
298 |
|
|
|
238 |
# 1. Retrieval Task
|
239 |
# ========================
|
240 |
# Encode query
|
241 |
+
query_embeddings = model.encode(
|
242 |
sentences=["Overview of climate change impacts on coastal cities"],
|
243 |
task="retrieval",
|
244 |
prompt_name="query",
|
245 |
+
)
|
246 |
+
|
247 |
+
print(f"query_embeddings.shape = {query_embeddings.shape}")
|
248 |
|
249 |
# Encode passage (text)
|
250 |
+
passage_embeddings = model.encode(
|
251 |
sentences=[
|
252 |
"Climate change has led to rising sea levels, increased frequency of extreme weather events..."
|
253 |
],
|
254 |
task="retrieval",
|
255 |
prompt_name="passage",
|
256 |
+
)
|
257 |
+
|
258 |
+
print(f"passage_embeddings.shape = {passage_embeddings.shape}")
|
259 |
|
260 |
# Encode image/document
|
261 |
+
image_embeddings = model.encode(
|
262 |
sentences=["https://i.ibb.co/nQNGqL0/beach1.jpg"],
|
263 |
task="retrieval",
|
264 |
+
)
|
265 |
+
|
266 |
+
print(f"image_embeddings.shape = {image_embeddings.shape}")
|
267 |
|
268 |
# ========================
|
269 |
# 2. Text Matching Task
|
|
|
287 |
# ========================
|
288 |
|
289 |
# Encode query
|
290 |
+
query_embeddings = model.encode(
|
291 |
sentences=["Find a function that prints a greeting message to the console"],
|
292 |
task="code",
|
293 |
prompt_name="query",
|
|
|
299 |
task="code",
|
300 |
prompt_name="passage",
|
301 |
)
|
302 |
+
|
303 |
+
# ========================
|
304 |
+
# 4. Use multivectors
|
305 |
+
# ========================
|
306 |
+
|
307 |
+
multivector_text_embeddings = model.encode(
|
308 |
+
sentences=texts,
|
309 |
+
task="retrieval",
|
310 |
+
prompt_name="query",
|
311 |
+
return_multivector=True,
|
312 |
+
)
|
313 |
+
|
314 |
+
images = ["https://i.ibb.co/nQNGqL0/beach1.jpg", "https://i.ibb.co/r5w8hG8/beach2.jpg"]
|
315 |
+
|
316 |
+
multivector_image_embeddings = model.encode(
|
317 |
+
sentences=images,
|
318 |
+
task="retrieval",
|
319 |
+
return_multivector=True,
|
320 |
+
)
|
321 |
```
|
322 |
</details>
|
323 |
|