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)# pip install -U transformers accelerate # 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
Download checkpoints/step_95000/optimizer.bin from magicslabnu/clip_softmax_bert_base: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/magicslabnu/clip_softmax_bert_base/resolve/main/checkpoints/step_95000/optimizer.bin
- Command line
-
hf download hf://magicslabnu/clip_softmax_bert_base/checkpoints/step_95000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/magicslabnu/clip_softmax_bert_base/resolve/main/checkpoints/step_95000/optimizer.bin
876 MB
- Xet hash:
- 07ea24afdce92081aa02f1964b088fdbe24f9cafcce3c3045d4aad4acf455da9
- Size of remote file:
- 876 MB
- SHA256:
- 08d129b15c3b2a4b1ae352764ebccc5141f96ee2d7127d41f9925a1d2a5100d3
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