Text Classification
Transformers
Safetensors
saif_decision
feature-extraction
typed-decisions
decision-model
system-one
jev-compatible
tool-use
routing
classification
calibration
custom-code
custom_code
Instructions to use GyrTechnology/saif-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GyrTechnology/saif-4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GyrTechnology/saif-4b", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GyrTechnology/saif-4b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download serving/request.json from GyrTechnology/saif-4b: direct link, hf CLI and curl.
- Browser
- Download file 416 Bytes
-
https://huggingface.co/GyrTechnology/saif-4b/resolve/main/serving/request.json
- Command line
-
hf download hf://GyrTechnology/saif-4b/serving/request.json
-
curl -L -o request.json https://huggingface.co/GyrTechnology/saif-4b/resolve/main/serving/request.json
416 Bytes
| {"model":"saif-4b","state":{"message":"The delivery arrived on time and works well."},"questions":{"satisfied":{"type":"noul","instructions":"Is the customer satisfied?"},"intent":{"type":"choice","instructions":"Classify the message.","criteria":{"praise":"Positive feedback","complaint":"A problem"}},"sentiment":{"type":"score","instructions":"Rate the sentiment.","criteria":["negative","neutral","positive"]}}} | |