Feature Extraction
Transformers
PyTorch
Safetensors
English
bert
sentiment-analysis
text-classification
generic
sentiment-classification
text-embeddings-inference
Instructions to use numind/NuSentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numind/NuSentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="numind/NuSentiment")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("numind/NuSentiment") model = AutoModel.from_pretrained("numind/NuSentiment") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model
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## Usage
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## Model
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The base version of [e5-v2](https://huggingface.co/intfloat/e5-base-v2) finetunned on an annotated subset of [C4](https://huggingface.co/datasets/Numind/C4_sentiment-analysis). This model provides generic embedding for sentiment analysis. Embeddings can be used out of the box or fine-tuned on specific datasets.
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Blog post: https://www.numind.ai/blog/creating-task-specific-foundation-models-with-gpt-4
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## Usage
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