Text Classification
Transformers
PyTorch
Safetensors
English
bert
regression
text-embeddings-inference
Instructions to use morenolq/thext-ai-scibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use morenolq/thext-ai-scibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="morenolq/thext-ai-scibert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("morenolq/thext-ai-scibert") model = AutoModelForSequenceClassification.from_pretrained("morenolq/thext-ai-scibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from morenolq/thext-ai-scibert: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/morenolq/thext-ai-scibert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://morenolq/thext-ai-scibert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/morenolq/thext-ai-scibert/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 08492b83338adf41b430765da13e29e702f6629d0960f327abf118458c1bc40c
- Size of remote file:
- 440 MB
- SHA256:
- 12e479bfa6f810575a615ef1dbc2251c3db8b097912d621945b51f9db7320a13
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