Instructions to use generalagents/tiny-mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use generalagents/tiny-mistral with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="generalagents/tiny-mistral")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("generalagents/tiny-mistral") model = AutoModelForImageTextToText.from_pretrained("generalagents/tiny-mistral") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use generalagents/tiny-mistral with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "generalagents/tiny-mistral" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "generalagents/tiny-mistral", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/generalagents/tiny-mistral
- SGLang
How to use generalagents/tiny-mistral 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 "generalagents/tiny-mistral" \ --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": "generalagents/tiny-mistral", "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 "generalagents/tiny-mistral" \ --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": "generalagents/tiny-mistral", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use generalagents/tiny-mistral with Docker Model Runner:
docker model run hf.co/generalagents/tiny-mistral
Upload Mistral3ForConditionalGeneration
Browse files- config.json +46 -0
- generation_config.json +6 -0
- model.safetensors +3 -0
config.json
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{
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"architectures": [
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"Mistral3ForConditionalGeneration"
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],
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"dtype": "bfloat16",
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"image_token_index": 10,
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"model_type": "mistral3",
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"multimodal_projector_bias": false,
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"projector_hidden_act": "gelu",
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"spatial_merge_size": 2,
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"text_config": {
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"attention_dropout": 0.0,
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"head_dim": 32,
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"hidden_act": "silu",
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"hidden_size": 32,
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"initializer_range": 0.02,
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"intermediate_size": 128,
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"max_position_embeddings": 131072,
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"model_type": "mistral",
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"num_attention_heads": 1,
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"num_hidden_layers": 2,
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"num_key_value_heads": 1,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000000.0,
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"sliding_window": 2,
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"use_cache": true,
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"vocab_size": 131072
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},
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"transformers_version": "4.57.1",
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"vision_config": {
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"attention_dropout": 0.0,
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 32,
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"image_size": 1540,
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"initializer_range": 0.02,
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"intermediate_size": 128,
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"model_type": "pixtral",
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"num_attention_heads": 1,
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"num_channels": 3,
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"num_hidden_layers": 2,
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"patch_size": 14,
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"rope_theta": 10000.0
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},
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"vision_feature_layer": -1
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "4.57.1"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:13886fcc5327c5866842e51d14b48845fb3dd644c616aea8ec385d1ee2a5e2a9
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size 16964440
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