TeichAI/gemini-3-pro-preview-high-reasoning-250x
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How to use nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx with MLX:
# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm
# Generate text with mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx")
prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
text = generate(model, tokenizer, prompt=prompt, verbose=True)How to use nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx",
max_seq_length=2048,
)How to use nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx with MLX LM:
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx"
# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "nightmedia/Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx",
"messages": [
{"role": "user", "content": "Hello"}
]
}'Quantized model performance
q6 0.599,0.757,0.876,0.770,0.466,0.806,0.756
Brainwaves for regular vs 1000x models in the q6 quant
regular 0.594,0.746,0.881,0.779,0.464,0.816,0.751
1000x 0.599,0.757,0.876,0.770,0.466,0.806,0.756
Heretic ablation improved the model arc/arc_easy significantly, with minor drops in other places
-G
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Gemma-3-27b-it-HERETIC-Gemini-1000x-Deep-Reasoning-q6-mlx")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
6-bit
Base model
google/gemma-3-27b-pt