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episod
/
tt-tnt

Text Generation
Transformers
Safetensors
English
llama
blackhole
p150
tenstorrent
thin
trained-from-scratch
tt-metal
tt-model-cache
ttml
vllm
conversational
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use episod/tt-tnt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use episod/tt-tnt with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="episod/tt-tnt")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("episod/tt-tnt")
    model = AutoModelForCausalLM.from_pretrained("episod/tt-tnt", device_map="auto")
    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=256)
    print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use episod/tt-tnt with vLLM:

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

    How to use episod/tt-tnt 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 "episod/tt-tnt" \
        --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": "episod/tt-tnt",
    		"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 "episod/tt-tnt" \
            --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": "episod/tt-tnt",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use episod/tt-tnt with Docker Model Runner:

    docker model run hf.co/episod/tt-tnt
tt-tnt / wheels
101 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
episod's picture
episod
remove stale v5-fat metal/ tree and vendored wheels (300-324)
0c009f2 verified about 1 month ago
  • tt_tnt_models_closure-0.77.0-py3-none-any.whl
    734 kB
    xet
    tt-model package-thin tt-tnt (v6 thin) about 1 month ago
  • ttnn-0.77.0-cp312-cp312-manylinux_2_34_x86_64.whl
    78.5 MB
    xet
    tt-model package tt-tnt (self-contained) about 1 month ago
  • vllm-0.25.1+empty-cp312-cp312-linux_x86_64.whl
    22 MB
    xet
    tt-model package-thin tt-tnt (v6 thin) about 1 month ago
  • vllm_tt_plugin-0.1.0-py3-none-any.whl
    142 kB
    xet
    tt-model package tt-tnt (self-contained) about 1 month ago