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assskelad
/
smollm2-360M-sft_SmallThoughts

Text Generation
Transformers
TensorBoard
Safetensors
llama
Generated from Trainer
SmallDoge/SmallThoughts
trl
sft
conversational
text-generation-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use assskelad/smollm2-360M-sft_SmallThoughts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use assskelad/smollm2-360M-sft_SmallThoughts with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="assskelad/smollm2-360M-sft_SmallThoughts")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("assskelad/smollm2-360M-sft_SmallThoughts")
    model = AutoModelForCausalLM.from_pretrained("assskelad/smollm2-360M-sft_SmallThoughts")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    inputs = tokenizer.apply_chat_template(
    	messages,
    	add_generation_prompt=True,
    	tokenize=True,
    	return_dict=True,
    	return_tensors="pt",
    ).to(model.device)
    
    outputs = model.generate(**inputs, max_new_tokens=40)
    print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use assskelad/smollm2-360M-sft_SmallThoughts with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "assskelad/smollm2-360M-sft_SmallThoughts"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "assskelad/smollm2-360M-sft_SmallThoughts",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/assskelad/smollm2-360M-sft_SmallThoughts
  • SGLang

    How to use assskelad/smollm2-360M-sft_SmallThoughts 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 "assskelad/smollm2-360M-sft_SmallThoughts" \
        --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": "assskelad/smollm2-360M-sft_SmallThoughts",
    		"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 "assskelad/smollm2-360M-sft_SmallThoughts" \
            --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": "assskelad/smollm2-360M-sft_SmallThoughts",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use assskelad/smollm2-360M-sft_SmallThoughts with Docker Model Runner:

    docker model run hf.co/assskelad/smollm2-360M-sft_SmallThoughts
smollm2-360M-sft_SmallThoughts
729 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
assskelad's picture
assskelad
End of training
7b0eb51 verified about 1 year ago
  • runs
    End of training about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    1.68 kB
    End of training about 1 year ago
  • all_results.json
    390 Bytes
    End of training about 1 year ago
  • config.json
    809 Bytes
    End of training about 1 year ago
  • eval_results.json
    175 Bytes
    End of training about 1 year ago
  • generation_config.json
    117 Bytes
    Model save about 1 year ago
  • merges.txt
    466 kB
    Model save about 1 year ago
  • model.safetensors
    724 MB
    xet
    Model save about 1 year ago
  • special_tokens_map.json
    906 Bytes
    Model save about 1 year ago
  • tokenizer.json
    3.52 MB
    Model save about 1 year ago
  • tokenizer_config.json
    4.34 kB
    Model save about 1 year ago
  • train_results.json
    218 Bytes
    Model save about 1 year ago
  • trainer_state.json
    15.2 kB
    Model save about 1 year ago
  • training_args.bin

    Detected Pickle imports (10)

    • "transformers.trainer_utils.IntervalStrategy",
    • "transformers.trainer_utils.SchedulerType",
    • "transformers.trainer_utils.HubStrategy",
    • "accelerate.state.PartialState",
    • "src.config.SFTConfig",
    • "torch.device",
    • "transformers.trainer_pt_utils.AcceleratorConfig",
    • "accelerate.utils.dataclasses.DistributedType",
    • "transformers.training_args.OptimizerNames",
    • "transformers.trainer_utils.SaveStrategy"

    How to fix it?

    5.62 kB
    xet
    Model save about 1 year ago
  • vocab.json
    801 kB
    Model save about 1 year ago