metadata
language:
- en
license: apache-2.0
base_model: FutureMa/Eva-4B
tags:
- finance
- earnings-calls
- financial-nlp
- text-classification
- qwen3
- llm-as-judge
- distillation
- mlx
- mlx-my-repo
pipeline_tag: text-generation
library_name: transformers
spaces:
- FutureMa/financial-evasion-detection
alexgusevski/Eva-4B-mlx-2Bit
The Model alexgusevski/Eva-4B-mlx-2Bit was converted to MLX format from FutureMa/Eva-4B using mlx-lm version 0.29.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("alexgusevski/Eva-4B-mlx-2Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)