Instructions to use guan-wang/EBFM-FineWeb-160M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guan-wang/EBFM-FineWeb-160M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="guan-wang/EBFM-FineWeb-160M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("guan-wang/EBFM-FineWeb-160M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download token_bytes.pt from guan-wang/EBFM-FineWeb-160M: direct link, hf CLI and curl.
- Browser
- Download file 133 kB
-
https://huggingface.co/guan-wang/EBFM-FineWeb-160M/resolve/main/token_bytes.pt
- Command line
-
hf download hf://guan-wang/EBFM-FineWeb-160M/token_bytes.pt
-
curl -L -o token_bytes.pt https://huggingface.co/guan-wang/EBFM-FineWeb-160M/resolve/main/token_bytes.pt
133 kB
- Xet hash:
- 206cdddf9c97ac2cb108b21357292b8e4a75532b22fdd07a1f753a28794b2f04
- Size of remote file:
- 133 kB
- SHA256:
- 72e6403e2fd4ffb9aab2e359c58aea91c6d541521cfb32663b8aae21b598fe0c
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