Instructions to use WaiLwin/junior_agent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WaiLwin/junior_agent with Transformers:
# Load model directly from transformers import AutoTokenizer, DistilBertForMultiHeadClassification tokenizer = AutoTokenizer.from_pretrained("WaiLwin/junior_agent") model = DistilBertForMultiHeadClassification.from_pretrained("WaiLwin/junior_agent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download service_encoder.pkl from WaiLwin/junior_agent: direct link, hf CLI and curl.
- Browser
- Download file 296 Bytes
-
https://huggingface.co/WaiLwin/junior_agent/resolve/main/service_encoder.pkl
- Command line
-
hf download hf://WaiLwin/junior_agent/service_encoder.pkl
-
curl -L -o service_encoder.pkl https://huggingface.co/WaiLwin/junior_agent/resolve/main/service_encoder.pkl
296 Bytes
- Xet hash:
- 24ceb79fd88b5a9de949ea0d23597e10a955720e614e3e740521c1df7736fbd8
- Size of remote file:
- 296 Bytes
- SHA256:
- fefe23837c48a35e8ace0bd83be547506b4e4d979d71bd2591933dff63bde283
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.