OzzyGT / gemma_4_E4B_it_sdnq_dynamic_8bit

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Total runs: 16
24-hour runs: 2
7-day runs: 1
30-day runs: 6
Model's Last Updated: July 07 2026
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Introduction of gemma_4_E4B_it_sdnq_dynamic_8bit

Model Details of gemma_4_E4B_it_sdnq_dynamic_8bit

Gemma 4 E4B it SDNQ Dynamic INT8

This is an int8 quantized version of google/gemma-4-E4B-it using SDNQ (SD.Next Quantization) with the dynamic option, Hadamard Rotation and quantized embeddings.

Note: You need SDNQ v0.2.1 or superior (the quantized embeddings + Hadamard path requires the nn.Embedding fix that landed in 0.2.1).

Usage

Load it with transformers like the original model. You need to import sdnq first so it registers into the transformers quantizer registry — without it, loading fails with a size-mismatch error:

import sdnq  # registers the SDNQ quantizer into transformers
import torch
from transformers import AutoModelForImageTextToText, AutoProcessor

model_id = "OzzyGT/gemma_4_E4B_it_sdnq_dynamic_8bit"

processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForImageTextToText.from_pretrained(model_id, dtype=torch.bfloat16, device_map="cuda")

messages = [{"role": "user", "content": [{"type": "text", "text": "Explain quantization in one sentence."}]}]
inputs = processor.apply_chat_template(
    messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt"
).to(model.device)

out = model.generate(**inputs, max_new_tokens=256)
print(processor.decode(out[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True))

Runs of OzzyGT gemma_4_E4B_it_sdnq_dynamic_8bit on huggingface.co

16
Total runs
2
24-hour runs
5
3-day runs
1
7-day runs
6
30-day runs

More Information About gemma_4_E4B_it_sdnq_dynamic_8bit huggingface.co Model

More gemma_4_E4B_it_sdnq_dynamic_8bit license Visit here:

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gemma_4_E4B_it_sdnq_dynamic_8bit huggingface.co

gemma_4_E4B_it_sdnq_dynamic_8bit huggingface.co is an AI model on huggingface.co that provides gemma_4_E4B_it_sdnq_dynamic_8bit's model effect (), which can be used instantly with this OzzyGT gemma_4_E4B_it_sdnq_dynamic_8bit model. huggingface.co supports a free trial of the gemma_4_E4B_it_sdnq_dynamic_8bit model, and also provides paid use of the gemma_4_E4B_it_sdnq_dynamic_8bit. Support call gemma_4_E4B_it_sdnq_dynamic_8bit model through api, including Node.js, Python, http.

gemma_4_E4B_it_sdnq_dynamic_8bit huggingface.co Url

https://huggingface.co/OzzyGT/gemma_4_E4B_it_sdnq_dynamic_8bit

OzzyGT gemma_4_E4B_it_sdnq_dynamic_8bit online free

gemma_4_E4B_it_sdnq_dynamic_8bit huggingface.co is an online trial and call api platform, which integrates gemma_4_E4B_it_sdnq_dynamic_8bit's modeling effects, including api services, and provides a free online trial of gemma_4_E4B_it_sdnq_dynamic_8bit, you can try gemma_4_E4B_it_sdnq_dynamic_8bit online for free by clicking the link below.

OzzyGT gemma_4_E4B_it_sdnq_dynamic_8bit online free url in huggingface.co:

https://huggingface.co/OzzyGT/gemma_4_E4B_it_sdnq_dynamic_8bit

gemma_4_E4B_it_sdnq_dynamic_8bit install

gemma_4_E4B_it_sdnq_dynamic_8bit is an open source model from GitHub that offers a free installation service, and any user can find gemma_4_E4B_it_sdnq_dynamic_8bit on GitHub to install. At the same time, huggingface.co provides the effect of gemma_4_E4B_it_sdnq_dynamic_8bit install, users can directly use gemma_4_E4B_it_sdnq_dynamic_8bit installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

gemma_4_E4B_it_sdnq_dynamic_8bit install url in huggingface.co:

https://huggingface.co/OzzyGT/gemma_4_E4B_it_sdnq_dynamic_8bit

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OzzyGT
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