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")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FutureMa/Eva-4B-V2") model = AutoModelForCausalLM.from_pretrained("FutureMa/Eva-4B-V2") - Notebooks
- Google Colab
- Kaggle
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| <!-- X轴标签 (0-100) --> | |
| <text x="150" y="280" text-anchor="middle" font-family="Helvetica Neue, Arial, sans-serif" font-size="12" fill="#666">0</text> | |
| <text x="245" y="280" text-anchor="middle" font-family="Helvetica Neue, Arial, sans-serif" font-size="12" fill="#666">25</text> | |
| <text x="340" y="280" text-anchor="middle" font-family="Helvetica Neue, Arial, sans-serif" font-size="12" fill="#666">50</text> | |
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| <text x="340" y="310" text-anchor="middle" font-family="Helvetica Neue, Arial, sans-serif" font-size="14" font-weight="bold" fill="#333">Macro-F1 (%)</text> | |
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| <!-- Eva-4B (Full): 84.9% - 粉色突出 --> | |
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| <text x="478" y="72" font-family="Helvetica Neue, Arial, sans-serif" font-size="13" font-weight="bold" fill="#333">84.9%</text> | |
| <!-- Gemini 3 Flash: 84.64% - 最深蓝 --> | |
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| <text x="477" y="114" font-family="Helvetica Neue, Arial, sans-serif" font-size="13" fill="#666">84.6%</text> | |
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| <text x="476" y="156" font-family="Helvetica Neue, Arial, sans-serif" font-size="13" fill="#666">84.4%</text> | |
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| <!-- Y轴标签 (模型名称) --> | |
| <text x="140" y="72" text-anchor="end" font-family="Helvetica Neue, Arial, sans-serif" font-size="13" font-weight="bold" fill="#333">Eva-4B (Full)</text> | |
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