Text Generation
Transformers
Safetensors
English
gemma
quantization
4bit
causal-lm
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use codemajesty/gemma2b-4bit-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codemajesty/gemma2b-4bit-quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="codemajesty/gemma2b-4bit-quantized")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("codemajesty/gemma2b-4bit-quantized") model = AutoModelForCausalLM.from_pretrained("codemajesty/gemma2b-4bit-quantized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use codemajesty/gemma2b-4bit-quantized with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "codemajesty/gemma2b-4bit-quantized" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codemajesty/gemma2b-4bit-quantized", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/codemajesty/gemma2b-4bit-quantized
- SGLang
How to use codemajesty/gemma2b-4bit-quantized with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "codemajesty/gemma2b-4bit-quantized" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codemajesty/gemma2b-4bit-quantized", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "codemajesty/gemma2b-4bit-quantized" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codemajesty/gemma2b-4bit-quantized", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use codemajesty/gemma2b-4bit-quantized with Docker Model Runner:
docker model run hf.co/codemajesty/gemma2b-4bit-quantized
| Apache License | |
| Version 2.0, January 2004 | |
| http://www.apache.org/licenses/ | |
| TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION | |
| Licensed under the Apache License, Version 2.0 (the "License"); | |
| you may not use this file except in compliance with the License. | |
| You may obtain a copy of the License at | |
| http://www.apache.org/licenses/LICENSE-2.0 | |
| Unless required by applicable law or agreed to in writing, software | |
| distributed under the License is distributed on an "AS IS" BASIS, | |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| See the License for the specific language governing permissions and | |
| limitations under the License. |