Text Classification
sentence-transformers
Safetensors
Transformers
English
bert
natural-language-inference
nlp
model-card
text-embeddings-inference
Instructions to use agentlans/e5-small-v2-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use agentlans/e5-small-v2-nli with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("agentlans/e5-small-v2-nli") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use agentlans/e5-small-v2-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agentlans/e5-small-v2-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agentlans/e5-small-v2-nli") model = AutoModelForSequenceClassification.from_pretrained("agentlans/e5-small-v2-nli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from agentlans/e5-small-v2-nli: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/agentlans/e5-small-v2-nli/resolve/main/training_args.bin
- Command line
-
hf download hf://agentlans/e5-small-v2-nli/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/agentlans/e5-small-v2-nli/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 692fd110819b5fd3a3d5d1dfa65db8f83c88587ec38d9244e799d0ebff206b6b
- Size of remote file:
- 5.24 kB
- SHA256:
- b63c36ed509026faf09600c28aa4ee9b78cb74e2e3c3893ee3b20029be0e301f
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