metadata
base_model: TeichAI/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill
tags:
- text-generation-inference
- transformers
- unsloth
- mlx
- nvidia
- cascade
- lm-studio
license: apache-2.0
language:
- en
datasets:
- TeichAI/claude-4.5-opus-high-reasoning-250x
SiddhJagani/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill-mlx-Q6
The Model SiddhJagani/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill-mlx-Q6 was converted to MLX format from TeichAI/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill using mlx-lm version 0.28.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("SiddhJagani/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill-mlx-Q6")
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)