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 training_args.bin from San-Analytics/TicketIQ-MultiTask: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/San-Analytics/TicketIQ-MultiTask/resolve/main/training_args.bin
- Command line
-
hf download hf://San-Analytics/TicketIQ-MultiTask/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/San-Analytics/TicketIQ-MultiTask/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- e5b760ad868cf9946b98c19b3eb51246ca4333dbd68e8071581041be8fe352c3
- Size of remote file:
- 5.27 kB
- SHA256:
- eda3171f3ffeeaad328a48d3de527aa62859ccfaf0a7c8f4fcbd2aa80007fcf3
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