Text Generation
Transformers
Safetensors
PyTorch
English
mistral
merlinite
ibm
lab
labrador
labradorite
quantized
4-bit precision
AWQ
instruct
text-generation-inference
awq
Instructions to use solidrust/merlinite-7b-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use solidrust/merlinite-7b-AWQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="solidrust/merlinite-7b-AWQ")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("solidrust/merlinite-7b-AWQ") model = AutoModelForCausalLM.from_pretrained("solidrust/merlinite-7b-AWQ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use solidrust/merlinite-7b-AWQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "solidrust/merlinite-7b-AWQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "solidrust/merlinite-7b-AWQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/solidrust/merlinite-7b-AWQ
- SGLang
How to use solidrust/merlinite-7b-AWQ 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 "solidrust/merlinite-7b-AWQ" \ --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": "solidrust/merlinite-7b-AWQ", "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 "solidrust/merlinite-7b-AWQ" \ --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": "solidrust/merlinite-7b-AWQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use solidrust/merlinite-7b-AWQ with Docker Model Runner:
docker model run hf.co/solidrust/merlinite-7b-AWQ
update model card meta data
Browse files
README.md
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@@ -22,6 +22,23 @@ license: apache-2.0
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language:
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- en
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base_model: mistralai/Mistral-7B-v0.1
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---
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# ibm/merlinite-7b AWQ
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language:
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- en
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base_model: mistralai/Mistral-7B-v0.1
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library_name: transformers
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model_creator: ibm
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model_name: Cmerlinite-7b
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model_type: mistral
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inference: false
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prompt_template: '<|im_start|>system
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{system_message}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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'
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quantized_by: Suparious
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---
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# ibm/merlinite-7b AWQ
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