Instructions to use EslamAhmed/google_Job_data_tuned_trial_2_11-2-2022 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EslamAhmed/google_Job_data_tuned_trial_2_11-2-2022 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EslamAhmed/google_Job_data_tuned_trial_2_11-2-2022")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EslamAhmed/google_Job_data_tuned_trial_2_11-2-2022") model = AutoModelForMaskedLM.from_pretrained("EslamAhmed/google_Job_data_tuned_trial_2_11-2-2022") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1ee5202351ec57b6aea95b64ea98a6725074383734fecedd4d56e970d7beb0fb
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size 433381480
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