Text Generation
Transformers
Safetensors
English
llama
gptq
text-generation-inference
llama2
4-bit precision
Instructions to use aiplanet/effi-7b-gptq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aiplanet/effi-7b-gptq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aiplanet/effi-7b-gptq")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("aiplanet/effi-7b-gptq") model = AutoModelForMultimodalLM.from_pretrained("aiplanet/effi-7b-gptq") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use aiplanet/effi-7b-gptq with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aiplanet/effi-7b-gptq" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aiplanet/effi-7b-gptq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aiplanet/effi-7b-gptq
- SGLang
How to use aiplanet/effi-7b-gptq 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 "aiplanet/effi-7b-gptq" \ --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": "aiplanet/effi-7b-gptq", "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 "aiplanet/effi-7b-gptq" \ --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": "aiplanet/effi-7b-gptq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aiplanet/effi-7b-gptq with Docker Model Runner:
docker model run hf.co/aiplanet/effi-7b-gptq
Update README.md
Browse files
README.md
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@@ -30,15 +30,15 @@ effi 7b GPTQ is a quantized version of effi 7b whiich is a 7 billion parameter m
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### Qunatization Configuration
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- bits: 4,
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- damp_percent
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- dataset: "wikitext2",
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- desc_act: false,
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- group_size: 128,
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- modules_in_block_to_quantize: null,
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- quant_method: "gptq",
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- sym: true,
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- true_sequential: true
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### Example of usage
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```
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### Framework versions
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- Transformers 4.37.2
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- optimum 1.16.2
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- auto-gptq 0.6.0
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### Citation
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### Qunatization Configuration
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- **bits:** 4,
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- **damp_percent** 0.1,
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- **dataset:** "wikitext2",
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- **desc_act:** false,
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- **group_size:** 128,
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- **modules_in_block_to_quantize:** null,
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- **quant_method:** "gptq",
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- **sym:** true,
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- **true_sequential:** true
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### Example of usage
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```
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### Framework versions
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- **Transformers** 4.37.2
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- **optimum** 1.16.2
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- **auto-gptq** 0.6.0
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### Citation
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