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bimabk
/
environment_test_affine_text_ppo

Text Generation
PEFT
PyTorch
Safetensors
Transformers
lora
conversational
Model card Files Files and versions
xet
Community

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

  • Libraries
  • PEFT

    How to use bimabk/environment_test_affine_text_ppo with PEFT:

    Base model is not found.
  • Transformers

    How to use bimabk/environment_test_affine_text_ppo with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="bimabk/environment_test_affine_text_ppo")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("bimabk/environment_test_affine_text_ppo", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use bimabk/environment_test_affine_text_ppo with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "bimabk/environment_test_affine_text_ppo"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "bimabk/environment_test_affine_text_ppo",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/bimabk/environment_test_affine_text_ppo
  • SGLang

    How to use bimabk/environment_test_affine_text_ppo 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 "bimabk/environment_test_affine_text_ppo" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "bimabk/environment_test_affine_text_ppo",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    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 "bimabk/environment_test_affine_text_ppo" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "bimabk/environment_test_affine_text_ppo",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use bimabk/environment_test_affine_text_ppo with Docker Model Runner:

    docker model run hf.co/bimabk/environment_test_affine_text_ppo
environment_test_affine_text_ppo
86.3 MB
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  • 1 contributor
History: 3 commits
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bimabk
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c22314a verified 3 months ago
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  • README.md
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  • adapter_config.json
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  • adapter_model.safetensors
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  • added_tokens.json
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  • chat_template.jinja
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  • loss.txt
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  • merges.txt
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  • ppo_save_info.json
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage",
    • "collections.OrderedDict"

    What is a pickle import?

    5.53 kB
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  • special_tokens_map.json
    613 Bytes
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
    4.71 kB
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  • vocab.json
    2.78 MB
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