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thrunlab
/
pretraining_test

Text Generation
Transformers
Safetensors
mistral
Generated from Trainer
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use thrunlab/pretraining_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use thrunlab/pretraining_test with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="thrunlab/pretraining_test")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("thrunlab/pretraining_test")
    model = AutoModelForCausalLM.from_pretrained("thrunlab/pretraining_test")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use thrunlab/pretraining_test with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "thrunlab/pretraining_test"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "thrunlab/pretraining_test",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/thrunlab/pretraining_test
  • SGLang

    How to use thrunlab/pretraining_test 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 "thrunlab/pretraining_test" \
        --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": "thrunlab/pretraining_test",
    		"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 "thrunlab/pretraining_test" \
            --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": "thrunlab/pretraining_test",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use thrunlab/pretraining_test with Docker Model Runner:

    docker model run hf.co/thrunlab/pretraining_test
pretraining_test
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  • 1 contributor
History: 7 commits
lukeleeai's picture
lukeleeai
End of training
1d72d97 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    1.42 kB
    End of training about 2 years ago
  • adapter_config.json
    602 Bytes
    Training in progress, step 50 about 2 years ago
  • adapter_model.safetensors
    609 kB
    xet
    Training in progress, step 100 about 2 years ago
  • config.json
    560 Bytes
    End of training about 2 years ago
  • generation_config.json
    111 Bytes
    End of training about 2 years ago
  • model.safetensors
    16.6 MB
    xet
    End of training about 2 years ago
  • special_tokens_map.json
    437 Bytes
    Training in progress, step 50 about 2 years ago
  • tokenizer.json
    1.8 MB
    Training in progress, step 50 about 2 years ago
  • tokenizer_config.json
    918 Bytes
    Training in progress, step 50 about 2 years ago
  • training_args.bin

    Detected Pickle imports (8)

    • "accelerate.state.PartialState",
    • "transformers.trainer_utils.SchedulerType",
    • "transformers.trainer_utils.HubStrategy",
    • "transformers.training_args.TrainingArguments",
    • "torch.device",
    • "transformers.training_args.OptimizerNames",
    • "transformers.trainer_utils.IntervalStrategy",
    • "accelerate.utils.dataclasses.DistributedType"

    How to fix it?

    4.6 kB
    xet
    Training in progress, step 50 about 2 years ago