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
Download scheduler.pt from FutureMa/Eva-4B-V2: direct link, hf CLI and curl.
- Browser
- Download file 1.47 kB
-
https://huggingface.co/FutureMa/Eva-4B-V2/resolve/main/scheduler.pt
- Command line
-
hf download hf://FutureMa/Eva-4B-V2/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/FutureMa/Eva-4B-V2/resolve/main/scheduler.pt
1.47 kB
- Xet hash:
- 2ff0c2923a05d50bc4b9890b268f77cc9ae5870294f178b54842e4ec04a59d8d
- Size of remote file:
- 1.47 kB
- SHA256:
- 26d2a2bf2d7b13984f8efee440ac376dc9aec135d539034d0f6ff7509ce14c7c
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