Instructions to use eduagarcia-temp/further_base_v4_1__checkpoint_last with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eduagarcia-temp/further_base_v4_1__checkpoint_last with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="eduagarcia-temp/further_base_v4_1__checkpoint_last")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("eduagarcia-temp/further_base_v4_1__checkpoint_last") model = AutoModelForMaskedLM.from_pretrained("eduagarcia-temp/further_base_v4_1__checkpoint_last", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eduagarcia-temp/further_base_v4_1__checkpoint_last: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/eduagarcia-temp/further_base_v4_1__checkpoint_last/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eduagarcia-temp/further_base_v4_1__checkpoint_last/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eduagarcia-temp/further_base_v4_1__checkpoint_last/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- bf4726e9b884732831266db1e1942e97f8e10a259d3bcc277c6e7cd1f5bc9dc2
- Size of remote file:
- 499 MB
- SHA256:
- df6494907f4a735ad7b2f7b7f2ed77114e8aa0e54a97e34b97b669f9687e689b
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