Text Classification
Transformers
Safetensors
PEFT
branchone
feature-extraction
decision-model
multimodal
custom-code
custom_code
Instructions to use ndemirdemir/BranchOne with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ndemirdemir/BranchOne with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ndemirdemir/BranchOne", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ndemirdemir/BranchOne", trust_remote_code=True, device_map="auto") - PEFT
How to use ndemirdemir/BranchOne with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download config.json from ndemirdemir/BranchOne: direct link, hf CLI and curl.
- Browser
- Download file 247 Bytes
-
https://huggingface.co/ndemirdemir/BranchOne/resolve/main/config.json
- Command line
-
hf download hf://ndemirdemir/BranchOne/config.json
-
curl -L -o config.json https://huggingface.co/ndemirdemir/BranchOne/resolve/main/config.json
247 Bytes
| { | |
| "model_type": "branchone", | |
| "architectures": [ | |
| "BranchOneModel" | |
| ], | |
| "branchone_format_version": 1, | |
| "auto_map": { | |
| "AutoConfig": "configuration_branchone.BranchOneConfig", | |
| "AutoModel": "modeling_branchone.BranchOneModel" | |
| } | |
| } | |