Feature Extraction
Transformers
Safetensors
English
gemma3_text
bnb-my-repo
text-generation-inference
unsloth
text-embeddings-inference
4-bit precision
bitsandbytes
Instructions to use ishu-newaz/Gemma3-1B-FP16-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ishu-newaz/Gemma3-1B-FP16-bnb-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ishu-newaz/Gemma3-1B-FP16-bnb-4bit")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ishu-newaz/Gemma3-1B-FP16-bnb-4bit") model = AutoModel.from_pretrained("ishu-newaz/Gemma3-1B-FP16-bnb-4bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use ishu-newaz/Gemma3-1B-FP16-bnb-4bit with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
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 ishu-newaz/Gemma3-1B-FP16-bnb-4bit to start chatting
Install Unsloth Studio (Windows)
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 ishu-newaz/Gemma3-1B-FP16-bnb-4bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ishu-newaz/Gemma3-1B-FP16-bnb-4bit to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="ishu-newaz/Gemma3-1B-FP16-bnb-4bit", max_seq_length=2048, )
ishu-newaz/Gemma3-1B-FP16 (Quantized)
Description
This model is a quantized version of the original model ishu-newaz/Gemma3-1B-FP16.
It's quantized using the BitsAndBytes library to 4-bit using the bnb-my-repo space.
Quantization Details
- Quantization Type: int4
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: bfloat16
- bnb_4bit_quant_storage: int8
๐ Original Model Information
Uploaded finetuned model
- Developed by: ishu-newaz
- License: apache-2.0
- Finetuned from model : unsloth/gemma-3-1b-it-unsloth-bnb-4bit
This gemma3_text model was trained 2x faster with Unsloth and Huggingface's TRL library.
- Downloads last month
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Model tree for ishu-newaz/Gemma3-1B-FP16-bnb-4bit
Base model
google/gemma-3-1b-pt Finetuned
google/gemma-3-1b-it Quantized
unsloth/gemma-3-1b-it-unsloth-bnb-4bit Finetuned
ishu-newaz/Gemma3-1B-FP16