Text Ranking
sentence-transformers
Safetensors
Transformers
new
text-classification
text-embeddings-inference
custom_code
Instructions to use Alibaba-NLP/gte-multilingual-reranker-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Alibaba-NLP/gte-multilingual-reranker-base with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("Alibaba-NLP/gte-multilingual-reranker-base", trust_remote_code=True) query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Transformers
How to use Alibaba-NLP/gte-multilingual-reranker-base with Transformers:
# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("Alibaba-NLP/gte-multilingual-reranker-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
support-tei
#11
by kozistr - opened
- add
id2label,label2idtoconfig.json. - remove
new.prefix from the key of the weight.
2024-11-17T10:45:42.615968Z INFO text_embeddings_router: router/src/main.rs:175: Args { model_id: "./gte-************-********-*ase", revision: None, tokenization_workers: None, dtype: Some(Float16), pooling: Some(Cls), max_concurrent_requests: 512, max_batch_tokens: 16384, max_batch_requests: None, max_client_batch_size: 32, auto_truncate: false, default_prompt_name: None, default_prompt: None, hf_api_token: None, hostname: "d58481309b13", port: 12345, uds_path: "/tmp/text-embeddings-inference-server", huggingface_hub_cache: None, payload_limit: 2000000, api_key: None, json_output: false, otlp_endpoint: None, otlp_service_name: "text-embeddings-inference.server", cors_allow_origin: None }
2024-11-17T10:45:42.616155Z WARN text_embeddings_router: router/src/lib.rs:377: `--pooling` arg is set but model is a classifier. Ignoring `--pooling` arg.
2024-11-17T10:45:43.253591Z WARN text_embeddings_router: router/src/lib.rs:202: Could not find a Sentence Transformers config
2024-11-17T10:45:43.253612Z INFO text_embeddings_router: router/src/lib.rs:206: Maximum number of tokens per request: 8192
2024-11-17T10:45:43.253626Z INFO text_embeddings_core::tokenization: core/src/tokenization.rs:28: Starting 4 tokenization workers
2024-11-17T10:45:44.723069Z INFO text_embeddings_router: router/src/lib.rs:248: Starting model backend
2024-11-17T10:45:44.930135Z INFO text_embeddings_backend_candle: backends/candle/src/lib.rs:354: Starting FlashGTE model on Cuda(CudaDevice(DeviceId(1)))
2024-11-17T10:45:54.536773Z INFO text_embeddings_router: router/src/lib.rs:264: Warming up model
2024-11-17T10:45:55.200022Z WARN text_embeddings_router: router/src/lib.rs:326: Invalid hostname, defaulting to 0.0.0.0
2024-11-17T10:45:55.202256Z INFO text_embeddings_router::http::server: router/src/http/server.rs:1812: Starting HTTP server: 0.0.0.0:12345
2024-11-17T10:45:55.202273Z INFO text_embeddings_router::http::server: router/src/http/server.rs:1813: Ready
kozistr changed pull request status to open
thenlper changed pull request status to merged