Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

tigerking009
/
ZOYA_FLASH_V1_PHASE0

Text Generation
Transformers
Safetensors
English
qwen3_5_text
abliterated
uncensored
qwen3.5
qwen
conversational
Model card Files Files and versions
xet
Community

Instructions to use tigerking009/ZOYA_FLASH_V1_PHASE0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tigerking009/ZOYA_FLASH_V1_PHASE0 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="tigerking009/ZOYA_FLASH_V1_PHASE0")
    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("tigerking009/ZOYA_FLASH_V1_PHASE0")
    model = AutoModelForCausalLM.from_pretrained("tigerking009/ZOYA_FLASH_V1_PHASE0", 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 tigerking009/ZOYA_FLASH_V1_PHASE0 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "tigerking009/ZOYA_FLASH_V1_PHASE0"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "tigerking009/ZOYA_FLASH_V1_PHASE0",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/tigerking009/ZOYA_FLASH_V1_PHASE0
  • SGLang

    How to use tigerking009/ZOYA_FLASH_V1_PHASE0 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 "tigerking009/ZOYA_FLASH_V1_PHASE0" \
        --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": "tigerking009/ZOYA_FLASH_V1_PHASE0",
    		"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 "tigerking009/ZOYA_FLASH_V1_PHASE0" \
            --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": "tigerking009/ZOYA_FLASH_V1_PHASE0",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use tigerking009/ZOYA_FLASH_V1_PHASE0 with Docker Model Runner:

    docker model run hf.co/tigerking009/ZOYA_FLASH_V1_PHASE0
ZOYA_FLASH_V1_PHASE0 / phase0
245 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 143 commits
tigerking009's picture
tigerking009
Lock fresh ZLL-R1 25-prompt benchmark pack
0785ead verified about 2 months ago
  • candidate_A3
    Save A3 Phase 0 benchmark and human evaluation about 2 months ago
  • candidate_A4
    Upload phase0/candidate_A4/human_eval/human_evaluation_report.json with huggingface_hub about 2 months ago
  • candidate_A5
    Phase 0 Step 5 A5 human evaluation update about 2 months ago
  • candidate_A6
    Archive A6 FLUX.1-schnell โ€” failed T4 speed gate; preserve smoke-test evidence about 2 months ago
  • candidate_A7_FINAL
    Finalize A7 SANA-Sprint Phase 0 benchmark and user-directed human evaluation about 2 months ago
  • candidate_A8_FINAL
    Finalize A8 SSD-1B LCM benchmark and user evaluation about 2 months ago
  • candidate_A9
    ZOYA Phase 0 Step 6 โ€” A9 Mage-Flow-Turbo final benchmark + human evaluation evidence about 2 months ago
  • fresh_benchmark
    Lock fresh ZLL-R1 25-prompt benchmark pack about 2 months ago
  • step1
    Add ZOYA-IMAGE-1 Phase 0 Step 1 A1 SDXL-Lightning screening packet about 2 months ago
  • step2
    Add A2 Hugging Face upload verification record about 2 months ago