Instructions to use magicslabnu/clip_softmax_bert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magicslabnu/clip_softmax_bert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="magicslabnu/clip_softmax_bert_base", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("magicslabnu/clip_softmax_bert_base", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("magicslabnu/clip_softmax_bert_base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8599e5bac4da525d8f327258d1a12081bd491fed8c0e2045df120d5493d4096f
- Size of remote file:
- 876 MB
- SHA256:
- 0df3e62068d0c6adbdb1a6a358168976f1130e818131a3058e7cad3f4233bb1b
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