Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use datasetsANDmodels/occupation-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datasetsANDmodels/occupation-extraction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("datasetsANDmodels/occupation-extraction") model = AutoModelForSeq2SeqLM.from_pretrained("datasetsANDmodels/occupation-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| import json | |
| import asyncio | |
| import websockets | |
| from transformers import pipeline | |
| extractor5 = pipeline("text2text-generation", model="occ_extract") | |
| async def occ_extractor(websocket, path): | |
| try: | |
| while True: | |
| data = await websocket.recv() | |
| payload = json.loads(data) | |
| intent = payload["prompt"] | |
| label=extractor5(intent)[0]["generated_text"] | |
| if label=="": | |
| label="No occupation detected" | |
| await websocket.send(json.dumps(label)) | |
| except websockets.ConnectionClosed: | |
| print("Connection closed") | |
| async def start_server(): | |
| server2 = await websockets.serve(occ_extractor, "0.0.0.0", 8766) | |
| print("Server task started") | |
| await asyncio.Future() | |
| asyncio.run(start_server()) | |