Text Generation
GGUF
English
Chinese
rocmfpx
rocmfp4
amd
rocm
strix-halo
quantized
humanizer
text-rewriting
gemma4
imatrix
conversational
Instructions to use Harsha001/humanizer-12b-ROCmFPX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Harsha001/humanizer-12b-ROCmFPX with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP # Run inference directly in the terminal: llama cli -hf Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP # Run inference directly in the terminal: llama cli -hf Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP # Run inference directly in the terminal: ./llama-cli -hf Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP # Run inference directly in the terminal: ./build/bin/llama-cli -hf Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
Use Docker
docker model run hf.co/Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
- Llama new
- LM Studio
- Jan
- vLLM
How to use Harsha001/humanizer-12b-ROCmFPX with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Harsha001/humanizer-12b-ROCmFPX" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Harsha001/humanizer-12b-ROCmFPX", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
- Ollama
How to use Harsha001/humanizer-12b-ROCmFPX with Ollama:
ollama run hf.co/Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
- Unsloth Desktop
- Docker Model Runner
How to use Harsha001/humanizer-12b-ROCmFPX with Docker Model Runner:
docker model run hf.co/Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
- Lemonade
How to use Harsha001/humanizer-12b-ROCmFPX with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Harsha001/humanizer-12b-ROCmFPX:Q4_0_ROCMFP
Run and chat with the model
lemonade run user.humanizer-12b-ROCmFPX-Q4_0_ROCMFP
List all available models
lemonade list
- Atomic Chat
Download prompt_format.json from Harsha001/humanizer-12b-ROCmFPX: direct link, hf CLI and curl.
- Browser
- Download file 553 Bytes
-
https://huggingface.co/Harsha001/humanizer-12b-ROCmFPX/resolve/main/prompt_format.json
- Command line
-
hf download hf://Harsha001/humanizer-12b-ROCmFPX/prompt_format.json
-
curl -L -o prompt_format.json https://huggingface.co/Harsha001/humanizer-12b-ROCmFPX/resolve/main/prompt_format.json
553 Bytes
| { | |
| "style": "legacy", | |
| "sep": "\n\n### Rewritten:\n\n", | |
| "fingerprint": "cc51d66b4c593fbe", | |
| "instr": "Rewrite the text below so it reads like a person wrote it, not a language model.\n\nReorganize it as you see fit. Vary sentence length on purpose. Cut hedging,\nthroat-clearing, and any sentence that only announces what comes next.\nPrefer the concrete word over the abstract one. It is fine to sound uneven.\n\nEvery fact, number, unit, date, name and quotation must survive unchanged.", | |
| "chat": false, | |
| "note": "推理时需 instr + draft + sep" | |
| } |