Instructions to use srini19/flair-tars-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srini19/flair-tars-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="srini19/flair-tars-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("srini19/flair-tars-base") model = AutoModel.from_pretrained("srini19/flair-tars-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from srini19/flair-tars-base: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/srini19/flair-tars-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://srini19/flair-tars-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/srini19/flair-tars-base/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 2229e1c2c691fa30fc85469cfa311050a005f84485d915cfd7514a78b04661dd
- Size of remote file:
- 1.63 GB
- SHA256:
- 578922bf87d8eb2f62122e160e28d021ea97f766ad786f39af239e797dd86dce
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