Text Generation
Transformers
Safetensors
GGUF
llama
chatbot
multilingual
arabic
french
tamazight
english
conversational
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use kaisser/LLM-Maroc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaisser/LLM-Maroc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="kaisser/LLM-Maroc") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("kaisser/LLM-Maroc") model = AutoModelForCausalLM.from_pretrained("kaisser/LLM-Maroc", 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=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kaisser/LLM-Maroc 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 kaisser/LLM-Maroc:BF16 # Run inference directly in the terminal: llama cli -hf kaisser/LLM-Maroc:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf kaisser/LLM-Maroc:BF16 # Run inference directly in the terminal: llama cli -hf kaisser/LLM-Maroc:BF16
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 kaisser/LLM-Maroc:BF16 # Run inference directly in the terminal: ./llama-cli -hf kaisser/LLM-Maroc:BF16
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 kaisser/LLM-Maroc:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf kaisser/LLM-Maroc:BF16
Use Docker
docker model run hf.co/kaisser/LLM-Maroc:BF16
- LM Studio
- Jan
- vLLM
How to use kaisser/LLM-Maroc with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kaisser/LLM-Maroc" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kaisser/LLM-Maroc", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/kaisser/LLM-Maroc:BF16
- SGLang
How to use kaisser/LLM-Maroc 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 "kaisser/LLM-Maroc" \ --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": "kaisser/LLM-Maroc", "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 "kaisser/LLM-Maroc" \ --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": "kaisser/LLM-Maroc", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use kaisser/LLM-Maroc with Ollama:
ollama run hf.co/kaisser/LLM-Maroc:BF16
- Unsloth Desktop
- Docker Model Runner
How to use kaisser/LLM-Maroc with Docker Model Runner:
docker model run hf.co/kaisser/LLM-Maroc:BF16
- Lemonade
How to use kaisser/LLM-Maroc with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kaisser/LLM-Maroc:BF16
Run and chat with the model
lemonade run user.LLM-Maroc-BF16
List all available models
lemonade list
- Atomic Chat
| # This is a basic version file for the Config-mode of find_package(). | |
| # It is used by write_basic_package_version_file() as input file for configure_file() | |
| # to create a version-file which can be installed along a config.cmake file. | |
| # | |
| # The created file sets PACKAGE_VERSION_EXACT if the current version string and | |
| # the requested version string are exactly the same and it sets | |
| # PACKAGE_VERSION_COMPATIBLE if the current version is >= requested version, | |
| # but only if the requested major version is the same as the current one. | |
| # The variable CVF_VERSION must be set before calling configure_file(). | |
| set(PACKAGE_VERSION "0.0.5923") | |
| if(PACKAGE_VERSION VERSION_LESS PACKAGE_FIND_VERSION) | |
| set(PACKAGE_VERSION_COMPATIBLE FALSE) | |
| else() | |
| if("0.0.5923" MATCHES "^([0-9]+)\\.") | |
| set(CVF_VERSION_MAJOR "${CMAKE_MATCH_1}") | |
| if(NOT CVF_VERSION_MAJOR VERSION_EQUAL 0) | |
| string(REGEX REPLACE "^0+" "" CVF_VERSION_MAJOR "${CVF_VERSION_MAJOR}") | |
| endif() | |
| else() | |
| set(CVF_VERSION_MAJOR "0.0.5923") | |
| endif() | |
| if(PACKAGE_FIND_VERSION_RANGE) | |
| # both endpoints of the range must have the expected major version | |
| math (EXPR CVF_VERSION_MAJOR_NEXT "${CVF_VERSION_MAJOR} + 1") | |
| if (NOT PACKAGE_FIND_VERSION_MIN_MAJOR STREQUAL CVF_VERSION_MAJOR | |
| OR ((PACKAGE_FIND_VERSION_RANGE_MAX STREQUAL "INCLUDE" AND NOT PACKAGE_FIND_VERSION_MAX_MAJOR STREQUAL CVF_VERSION_MAJOR) | |
| OR (PACKAGE_FIND_VERSION_RANGE_MAX STREQUAL "EXCLUDE" AND NOT PACKAGE_FIND_VERSION_MAX VERSION_LESS_EQUAL CVF_VERSION_MAJOR_NEXT))) | |
| set(PACKAGE_VERSION_COMPATIBLE FALSE) | |
| elseif(PACKAGE_FIND_VERSION_MIN_MAJOR STREQUAL CVF_VERSION_MAJOR | |
| AND ((PACKAGE_FIND_VERSION_RANGE_MAX STREQUAL "INCLUDE" AND PACKAGE_VERSION VERSION_LESS_EQUAL PACKAGE_FIND_VERSION_MAX) | |
| OR (PACKAGE_FIND_VERSION_RANGE_MAX STREQUAL "EXCLUDE" AND PACKAGE_VERSION VERSION_LESS PACKAGE_FIND_VERSION_MAX))) | |
| set(PACKAGE_VERSION_COMPATIBLE TRUE) | |
| else() | |
| set(PACKAGE_VERSION_COMPATIBLE FALSE) | |
| endif() | |
| else() | |
| if(PACKAGE_FIND_VERSION_MAJOR STREQUAL CVF_VERSION_MAJOR) | |
| set(PACKAGE_VERSION_COMPATIBLE TRUE) | |
| else() | |
| set(PACKAGE_VERSION_COMPATIBLE FALSE) | |
| endif() | |
| if(PACKAGE_FIND_VERSION STREQUAL PACKAGE_VERSION) | |
| set(PACKAGE_VERSION_EXACT TRUE) | |
| endif() | |
| endif() | |
| endif() | |
| # if the installed or the using project don't have CMAKE_SIZEOF_VOID_P set, ignore it: | |
| if("${CMAKE_SIZEOF_VOID_P}" STREQUAL "" OR "8" STREQUAL "") | |
| return() | |
| endif() | |
| # check that the installed version has the same 32/64bit-ness as the one which is currently searching: | |
| if(NOT CMAKE_SIZEOF_VOID_P STREQUAL "8") | |
| math(EXPR installedBits "8 * 8") | |
| set(PACKAGE_VERSION "${PACKAGE_VERSION} (${installedBits}bit)") | |
| set(PACKAGE_VERSION_UNSUITABLE TRUE) | |
| endif() | |