Text Classification
Transformers
Safetensors
English
bert
nlp
routing
vision-task-classifier
text-embeddings-inference
Instructions to use beingamanforever/ICM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beingamanforever/ICM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="beingamanforever/ICM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, TaskClassifier tokenizer = AutoTokenizer.from_pretrained("beingamanforever/ICM") model = TaskClassifier.from_pretrained("beingamanforever/ICM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-180/tokenizer.json from beingamanforever/ICM: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/beingamanforever/ICM/resolve/main/checkpoint-180/tokenizer.json
- Command line
-
hf download hf://beingamanforever/ICM/checkpoint-180/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/beingamanforever/ICM/resolve/main/checkpoint-180/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.