Image Feature Extraction
Transformers
Safetensors
English
arcee_kda
kda
kimi-delta-attention
linear-attention
nope
hybrid-attention
distillation
research
custom_code
Instructions to use arcee-ai/AFM-4.5B-Base-KDA-NoPE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arcee-ai/AFM-4.5B-Base-KDA-NoPE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="arcee-ai/AFM-4.5B-Base-KDA-NoPE", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("arcee-ai/AFM-4.5B-Base-KDA-NoPE", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cb6ca1a747d1927111d842f9ffce8000e58b58b836a36a96da7a65cb27884ac
- Size of remote file:
- 4.91 GB
- SHA256:
- 14597f2522c865f8cd60ed3c933059898d2d472ed2c602f6251922b988266797
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