Text Classification
Transformers
TensorBoard
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use lomov/strategydisofmaterialimpactsv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lomov/strategydisofmaterialimpactsv1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lomov/strategydisofmaterialimpactsv1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lomov/strategydisofmaterialimpactsv1") model = AutoModelForSequenceClassification.from_pretrained("lomov/strategydisofmaterialimpactsv1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f23c5c309f0fafd6fd9b85c509f072c7ef962947751e8ecbd0802b9d357f0841
- Size of remote file:
- 5.05 kB
- SHA256:
- 00eabf4077e94e757a3dc41c77d7c9af42e5254ef980f361fda4b5753e5f8829
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