Instructions to use mnaylor/psychbert-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mnaylor/psychbert-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mnaylor/psychbert-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mnaylor/psychbert-cased") model = AutoModelForMaskedLM.from_pretrained("mnaylor/psychbert-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from mnaylor/psychbert-cased: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/mnaylor/psychbert-cased/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://mnaylor/psychbert-cased/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/mnaylor/psychbert-cased/resolve/main/flax_model.msgpack
433 MB
- Xet hash:
- 4427bc64c3dcf23f985f5928085ff2f5d0fc6baf633081434690d4cea5526a38
- Size of remote file:
- 433 MB
- SHA256:
- fa9922fcba7adb4a0379371da339d27c88c76650ec8cefe3abd6961822f13b9c
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