🤖 A gateway to Hugging Face's Inference API
You can perform various NLP tasks using different models. The gateway supports multiple tasks, including feature extraction, text classification, token classification, question answering, summarization, translation, text generation, and sentence similarity.
- Feature Extraction: Extract features from text using models like
BAAI/bge-base-en-v1.5
.
- Text Classification: Classify text sentiment, emotions, etc., using models like
j-hartmann/emotion-english-distilroberta-base
.
- Token Classification: Perform named entity recognition (NER) and other token-level classifications.
- Question Answering: Answer questions based on a given context.
- Summarization: Generate summaries of longer texts.
- Translation: Translate text from one language to another.
- Text Generation: Generate text based on a given prompt.
- Sentence Similarity: Calculate semantic similarity between sentences.
Send a POST request with the required inputs to the endpoint with the appropriate task and model parameters.
Or use the default models.
# Example Default Model Request
curl -X POST -H "Content-Type: application/json" -d '{"inputs": {"source_sentence": "Hello World", "sentences": ["Goodbye World", "How are you?", "Nice to meet you."]}}' "https://iamseeley-hfapigateway.web.val.run/?task=feature-extraction"
Feature Extraction
curl -X POST -H "Content-Type: application/json" -d '{"inputs": ["Hello World", "Goodbye World"]}' "https://iamseeley-hfapigateway.web.val.run/?task=feature-extraction&model=BAAI/bge-base-en-v1.5"
Feature Extraction
curl -X POST -H "Content-Type: application/json" -d '{"inputs": {"source_sentence": "Hello World", "sentences": ["Goodbye World", "How are you?", "Nice to meet you."]}}' "https://iamseeley-hfapigateway.web.val.run/?task=feature-extraction&model=sentence-transformers/all-MiniLM-L6-v2"
Text Classification
curl -X POST -H "Content-Type: application/json" -d '{"inputs": "I love programming!"}' "https://iamseeley-hfapigateway.web.val.run/?task=text-classification&model=j-hartmann/emotion-english-distilroberta-base"
Token Classification
curl -X POST -H "Content-Type: application/json" -d '{"inputs": "My name is John and I live in New York."}' "https://iamseeley-hfApiGateway.web.val.run/?task=token-classification&model=dbmdz/bert-large-cased-finetuned-conll03-english"
Question Answering
curl -X POST -H "Content-Type: application/json" -d '{"inputs": {"question": "What is the capital of France?", "context": "The capital of France is Paris, a major European city and a global center for art, fashion, gastronomy, and culture."}}' "https://iamseeley-hfapigateway.web.val.run/?task=question-answering&model=deepset/roberta-base-squad2"
Summarization
curl -X POST -H "Content-Type: application/json" -d '{"inputs": "The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New York City was finished in 1930. It was the first structure to reach a height of 300 metres. Due to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler Building by 5.2 metres (17 ft). Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct."}' "https://iamseeley-hfapigateway.web.val.run/?task=summarization&model=sshleifer/distilbart-cnn-12-6"
Translation
curl -X POST -H "Content-Type: application/json" -d '{"inputs": "Hello, how are you?"}' "https://iamseeley-hfapigateway.web.val.run/?task=translation&model=google-t5/t5-small"
Text Generation
curl -X POST -H "Content-Type: application/json" -d '{"inputs": "Once upon a time"}' "https://iamseeley-hfapigateway.web.val.run/?task=text-generation&model=gpt2"
Sentence Similarity
curl -X POST -H "Content-Type: application/json" -d '{"inputs": {"source_sentence": "Hello World", "sentences": ["Goodbye World"]}}' "https://iamseeley-hfapigateway.web.val.run/?task=sentence-similarity&model=sentence-transformers/all-MiniLM-L6-v2"
Val Examples Using Pipeline
import Pipeline from "https://esm.town/v/iamseeley/pipeline";
}
else if (req.
method ===
"POST") {
const { inputs } =
await req.
json();
const pipeline =
new Pipeline(
"task",
"model");
const result =
await pipeline.
run(inputs);
return new Response(
JSON.
stringify(result), {
headers: {
"Content-Type":
"application/json" } });
}
}
exampleTranslation
exampleTextClassification
exampleFeatureExtraction
exampleTextGeneration
exampleSummarization
exampleQuestionAnswering
is there a way to do this with huggingface spaces? or is that not a thing