Instructions to use improz4/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use improz4/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="improz4/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("improz4/model") model = AutoModelForMaskedLM.from_pretrained("improz4/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from improz4/model: direct link, hf CLI and curl.
- Browser
- Download file 30.3 MB
-
https://huggingface.co/improz4/model/resolve/8a2499e7ca88ea1df16bf245aaa2a6720ee02b83/pytorch_model.bin
- Command line
-
hf download hf://improz4/model@8a2499e7ca88ea1df16bf245aaa2a6720ee02b83/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/improz4/model/resolve/8a2499e7ca88ea1df16bf245aaa2a6720ee02b83/pytorch_model.bin
30.3 MB
- Xet hash:
- 42fea4ac2bb5e59006df5d28c28ba8e5f0457e084ab4e985221338c39fe2f51a
- Size of remote file:
- 30.3 MB
- SHA256:
- 51eba0cf014d2a38060b0494e24325b0024257538d868fad4881bc3a07d87287
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