Instructions to use TJMUCH/transcriptome-iseeek with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TJMUCH/transcriptome-iseeek with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="TJMUCH/transcriptome-iseeek")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("TJMUCH/transcriptome-iseeek") model = AutoModelForMaskedLM.from_pretrained("TJMUCH/transcriptome-iseeek", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TJMUCH/transcriptome-iseeek: direct link, hf CLI and curl.
- Browser
- Download file 149 MB
-
https://huggingface.co/TJMUCH/transcriptome-iseeek/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TJMUCH/transcriptome-iseeek/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TJMUCH/transcriptome-iseeek/resolve/main/pytorch_model.bin
149 MB
- Xet hash:
- a2085d51fc45fca6c328bfdf779bc6c947f6a0ceacbd39c8da408da510407ad7
- Size of remote file:
- 149 MB
- SHA256:
- fc8f82423612e372ddcd26ead16df7b2543749e7569b3d455c0e4793fe7ac548
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