Feature Extraction
Transformers
TensorBoard
Safetensors
English
captionbert_v2
sentence-similarity
consensus-distillation
geometric-deep-learning
amoe
custom_code
Instructions to use AbstractPhil/captionbert-8192-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AbstractPhil/captionbert-8192-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AbstractPhil/captionbert-8192-v2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AbstractPhil/captionbert-8192-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoints/tokenizer/tokenizer.json from AbstractPhil/captionbert-8192-v2: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/AbstractPhil/captionbert-8192-v2/resolve/main/checkpoints/tokenizer/tokenizer.json
- Command line
-
hf download hf://AbstractPhil/captionbert-8192-v2/checkpoints/tokenizer/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/AbstractPhil/captionbert-8192-v2/resolve/main/checkpoints/tokenizer/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.