Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use RavingRabbit/eformConsult with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RavingRabbit/eformConsult with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RavingRabbit/eformConsult")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RavingRabbit/eformConsult") model = AutoModelForSequenceClassification.from_pretrained("RavingRabbit/eformConsult", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download run-1/checkpoint-1069/optimizer.pt from RavingRabbit/eformConsult: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/RavingRabbit/eformConsult/resolve/main/run-1/checkpoint-1069/optimizer.pt
- Command line
-
hf download hf://RavingRabbit/eformConsult/run-1/checkpoint-1069/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/RavingRabbit/eformConsult/resolve/main/run-1/checkpoint-1069/optimizer.pt
536 MB
- Xet hash:
- 3195c86eb60a39c9c236963672df44063eace3be7590ee1488451f3369594e11
- Size of remote file:
- 536 MB
- SHA256:
- 0114b256fa0583b7253e66b193409761bb919ccae414af61fd12e26cd7a0fffc
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