Text Classification
Transformers
Safetensors
PEFT
English
roberta
nlp
lora
multitask-learning
customer-support
text-embeddings-inference
Instructions to use San-Analytics/TicketIQ-MultiTask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use San-Analytics/TicketIQ-MultiTask with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="San-Analytics/TicketIQ-MultiTask")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("San-Analytics/TicketIQ-MultiTask") model = AutoModelForSequenceClassification.from_pretrained("San-Analytics/TicketIQ-MultiTask", device_map="auto") - PEFT
How to use San-Analytics/TicketIQ-MultiTask with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from San-Analytics/TicketIQ-MultiTask: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/San-Analytics/TicketIQ-MultiTask/resolve/main/tokenizer.json
- Command line
-
hf download hf://San-Analytics/TicketIQ-MultiTask/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/San-Analytics/TicketIQ-MultiTask/resolve/main/tokenizer.json
3.56 MB
File too large to display, you can check the raw version instead.