Instructions to use SeanScripts/pixtral-12b-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SeanScripts/pixtral-12b-nf4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="SeanScripts/pixtral-12b-nf4")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("SeanScripts/pixtral-12b-nf4") model = AutoModelForImageTextToText.from_pretrained("SeanScripts/pixtral-12b-nf4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SeanScripts/pixtral-12b-nf4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SeanScripts/pixtral-12b-nf4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SeanScripts/pixtral-12b-nf4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SeanScripts/pixtral-12b-nf4
- SGLang
How to use SeanScripts/pixtral-12b-nf4 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 "SeanScripts/pixtral-12b-nf4" \ --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": "SeanScripts/pixtral-12b-nf4", "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 "SeanScripts/pixtral-12b-nf4" \ --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": "SeanScripts/pixtral-12b-nf4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SeanScripts/pixtral-12b-nf4 with Docker Model Runner:
docker model run hf.co/SeanScripts/pixtral-12b-nf4
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| "_name_or_path": "./pixtral-12b", | |
| "architectures": [ | |
| "LlavaForConditionalGeneration" | |
| ], | |
| "ignore_index": -100, | |
| "image_seq_length": 1, | |
| "image_token_index": 10, | |
| "model_type": "llava", | |
| "projector_hidden_act": "gelu", | |
| "quantization_config": { | |
| "_load_in_4bit": true, | |
| "_load_in_8bit": false, | |
| "bnb_4bit_compute_dtype": "bfloat16", | |
| "bnb_4bit_quant_storage": "uint8", | |
| "bnb_4bit_quant_type": "nf4", | |
| "bnb_4bit_use_double_quant": false, | |
| "llm_int8_enable_fp32_cpu_offload": false, | |
| "llm_int8_has_fp16_weight": false, | |
| "llm_int8_skip_modules": null, | |
| "llm_int8_threshold": 6.0, | |
| "load_in_4bit": true, | |
| "load_in_8bit": false, | |
| "quant_method": "bitsandbytes" | |
| }, | |
| "text_config": { | |
| "_name_or_path": "", | |
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| "model_type": "mistral", | |
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| "use_cache": true, | |
| "vocab_size": 131072 | |
| }, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.45.0.dev0", | |
| "vision_config": { | |
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| "id2label": { | |
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| "1": "LABEL_1" | |
| }, | |
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| "num_channels": 3, | |
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| "output_attentions": false, | |
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| "output_scores": false, | |
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| "patch_size": 16, | |
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| "vision_feature_select_strategy": "full" | |
| } | |