Instructions to use bertin-project/bertin-base-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertin-project/bertin-base-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bertin-project/bertin-base-random")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-random") model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-base-random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download mc4-es-train-50M-random-stats.csv.tar.gz from bertin-project/bertin-base-random: direct link, hf CLI and curl.
- Browser
- Download file 551 MB
-
https://huggingface.co/bertin-project/bertin-base-random/resolve/main/mc4-es-train-50M-random-stats.csv.tar.gz
- Command line
-
hf download hf://bertin-project/bertin-base-random/mc4-es-train-50M-random-stats.csv.tar.gz
-
curl -L -o mc4-es-train-50M-random-stats.csv.tar.gz https://huggingface.co/bertin-project/bertin-base-random/resolve/main/mc4-es-train-50M-random-stats.csv.tar.gz
551 MB
- Xet hash:
- 9a2b4b3a68ecaf0547eb8915ed895438f3e8921357e026c3d31fe72d542c8673
- Size of remote file:
- 551 MB
- SHA256:
- 9a7bccebc85aad9471658bbdfeead54f282363c7e438d6c61c160a1e86272bb0
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