Instructions to use Qmed/llama_instruct_ipex-tcm-AMX-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Qmed/llama_instruct_ipex-tcm-AMX-bf16 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/home/qmed-intel/models/meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "Qmed/llama_instruct_ipex-tcm-AMX-bf16") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Qmed/llama_instruct_ipex-tcm-AMX-bf16 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 Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M # Run inference directly in the terminal: llama cli -hf Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M # Run inference directly in the terminal: llama cli -hf Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M
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 Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M
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 Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M
Use Docker
docker model run hf.co/Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Qmed/llama_instruct_ipex-tcm-AMX-bf16 with Ollama:
ollama run hf.co/Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Qmed/llama_instruct_ipex-tcm-AMX-bf16 with Docker Model Runner:
docker model run hf.co/Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M
- Lemonade
How to use Qmed/llama_instruct_ipex-tcm-AMX-bf16 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Qmed/llama_instruct_ipex-tcm-AMX-bf16:Q4_K_M
Run and chat with the model
lemonade run user.llama_instruct_ipex-tcm-AMX-bf16-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Upload folder using huggingface_hub
Upload folder using huggingface_hub
Multi commit ID: c5f98981fd281accb866a48114b3257816af0bb1699dd79378a42eb93cead1ad
Scheduled commits:
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This is a comment posted using the huggingface_hub library in the context of a multi-commit. Learn more about multi-commits in this guide.