Instructions to use eduagarcia-temp/cnj_v1_2__checkpoint_last with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eduagarcia-temp/cnj_v1_2__checkpoint_last with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="eduagarcia-temp/cnj_v1_2__checkpoint_last")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("eduagarcia-temp/cnj_v1_2__checkpoint_last") model = AutoModelForMaskedLM.from_pretrained("eduagarcia-temp/cnj_v1_2__checkpoint_last", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eduagarcia-temp/cnj_v1_2__checkpoint_last: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/eduagarcia-temp/cnj_v1_2__checkpoint_last/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eduagarcia-temp/cnj_v1_2__checkpoint_last/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eduagarcia-temp/cnj_v1_2__checkpoint_last/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- aed6658c27ddea111b11a08a13824b3cf65ee6ebbf5855a82ddbf9e04abe52d1
- Size of remote file:
- 499 MB
- SHA256:
- d50229dab14c6d4c07b19be4a5c4cd0bad189ac842a0686015f4d830f4b152d6
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