Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use raminass/M4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raminass/M4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="raminass/M4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("raminass/M4") model = AutoModelForSequenceClassification.from_pretrained("raminass/M4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57cb526010c4dbeb231dfd1910216cc5f06f7145973ce12d3da50a193d3c39a2
- Size of remote file:
- 4.86 kB
- SHA256:
- d4f6cc8005a48db960688564ade76e27b24419778d373200fdc0c5bdd9ffda65
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