Text Classification
Transformers
Safetensors
lfm2
liquid
lfm2.5
bidirectional
sequence-classification
encoder
custom_code
Instructions to use allura-forge/LFM2.5-Encoder-350M-SeqCls-initialized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allura-forge/LFM2.5-Encoder-350M-SeqCls-initialized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="allura-forge/LFM2.5-Encoder-350M-SeqCls-initialized", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("allura-forge/LFM2.5-Encoder-350M-SeqCls-initialized", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("allura-forge/LFM2.5-Encoder-350M-SeqCls-initialized", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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