Text Classification
Transformers
Safetensors
English
qwen3
text-generation
finance
earnings-calls
evasion-detection
nlp
Eval Results
text-embeddings-inference
Instructions to use FutureMa/Eva-4B-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FutureMa/Eva-4B-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FutureMa/Eva-4B-V2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FutureMa/Eva-4B-V2") model = AutoModelForCausalLM.from_pretrained("FutureMa/Eva-4B-V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download top5_performance.svg from FutureMa/Eva-4B-V2: direct link, hf CLI and curl.
- Browser
- Download file 3.84 kB
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https://huggingface.co/FutureMa/Eva-4B-V2/resolve/main/top5_performance.svg
- Command line
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hf download hf://FutureMa/Eva-4B-V2/top5_performance.svg
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curl -L -o top5_performance.svg https://huggingface.co/FutureMa/Eva-4B-V2/resolve/main/top5_performance.svg
3.84 kB