Feature Extraction
Transformers
Safetensors
modernbert
html
document-embedding
text-embeddings-inference
Instructions to use Seznam/html-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Seznam/html-lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Seznam/html-lm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Seznam/html-lm") model = AutoModel.from_pretrained("Seznam/html-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test/embedded.npy from Seznam/html-lm: direct link, hf CLI and curl.
- Browser
- Download file 3.2 kB
-
https://huggingface.co/Seznam/html-lm/resolve/main/test/embedded.npy
- Command line
-
hf download hf://Seznam/html-lm/test/embedded.npy
-
curl -L -o embedded.npy https://huggingface.co/Seznam/html-lm/resolve/main/test/embedded.npy
3.2 kB
- Xet hash:
- cfad1e66b5e269057a23464a47067422a76baa1e5083679670b2c511f9c547a4
- Size of remote file:
- 3.2 kB
- SHA256:
- 9bf47e68a2256aaca90de7fa111caffe741952c1eb38ddd346f89e1d16a29c97
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