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 Studio
How to use kaisser/LLM-Maroc with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kaisser/LLM-Maroc to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kaisser/LLM-Maroc to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for kaisser/LLM-Maroc to start chatting
- 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
| PROG=${0##*/} | |
| build_dir="build-ci-debug" | |
| # Print Color Commands | |
| red=$(tput setaf 1) | |
| green=$(tput setaf 2) | |
| yellow=$(tput setaf 3) | |
| blue=$(tput setaf 4) | |
| magenta=$(tput setaf 5) | |
| cyan=$(tput setaf 6) | |
| normal=$(tput sgr0) | |
| # Print Help Message | |
| #################### | |
| print_full_help() { | |
| cat << EOF | |
| Usage: $PROG [OPTION]... <test_regex> (test_number) | |
| Debug specific ctest program. | |
| Options: | |
| -h, --help display this help and exit | |
| -g run in gdb mode | |
| Arguments: | |
| <test_regex> (Mandatory) Supply one regex to the script to filter tests | |
| (test_number) (Optional) Test number to run a specific test | |
| Example: | |
| $PROG test-tokenizer | |
| $PROG test-tokenizer 3 | |
| EOF | |
| } | |
| abort() { | |
| echo "Error: $1" >&2 | |
| cat << EOF >&2 | |
| Usage: $PROG [OPTION]... <test_regex> (test_number) | |
| Debug specific ctest program. | |
| Refer to --help for full instructions. | |
| EOF | |
| exit 1 | |
| } | |
| # Dependency Sanity Check | |
| ######################### | |
| check_dependency() { | |
| command -v "$1" >/dev/null 2>&1 || { | |
| abort "$1 is required but not found. Please install it and try again." | |
| } | |
| } | |
| check_dependency ctest | |
| check_dependency cmake | |
| # Step 0: Check the args | |
| ######################## | |
| if [ x"$1" = x"-h" ] || [ x"$1" = x"--help" ]; then | |
| print_full_help >&2 | |
| exit 0 | |
| fi | |
| # Parse command-line options | |
| gdb_mode=false | |
| while getopts "g" opt; do | |
| case $opt in | |
| g) | |
| gdb_mode=true | |
| echo "gdb_mode Mode Enabled" | |
| ;; | |
| esac | |
| done | |
| # Shift the option parameters | |
| shift $((OPTIND - 1)) | |
| # Positionial Argument Processing : <test_regex> | |
| if [ -z "${1}" ]; then | |
| abort "Test regex is required" | |
| else | |
| test_suite=${1:-} | |
| fi | |
| # Positionial Argument Processing : (test_number) | |
| test_number=${2:-} | |
| # Step 1: Reset and Setup folder context | |
| ######################################## | |
| ## Sanity check that we are actually in a git repo | |
| repo_root=$(git rev-parse --show-toplevel) | |
| if [ ! -d "$repo_root" ]; then | |
| abort "Not in a Git repository." | |
| fi | |
| ## Reset folder to root context of git repo and Create and enter build directory | |
| pushd "$repo_root" | |
| rm -rf "$build_dir" && mkdir "$build_dir" || abort "Failed to make $build_dir" | |
| # Step 2: Setup Build Environment and Compile Test Binaries | |
| ########################################################### | |
| # Note: test-eval-callback requires -DLLAMA_CURL | |
| cmake -B "./$build_dir" -DCMAKE_BUILD_TYPE=Debug -DGGML_CUDA=1 -DLLAMA_CURL=1 || abort "Failed to build environment" | |
| pushd "$build_dir" | |
| make -j || abort "Failed to compile" | |
| popd > /dev/null || exit 1 | |
| # Step 3: Find all tests available that matches REGEX | |
| #################################################### | |
| # Ctest Gather Tests | |
| # `-R test-tokenizer` : looks for all the test files named `test-tokenizer*` (R=Regex) | |
| # `-N` : "show-only" disables test execution & shows test commands that you can feed to GDB. | |
| # `-V` : Verbose Mode | |
| printf "\n\nGathering tests that fit REGEX: ${test_suite} ...\n" | |
| pushd "$build_dir" | |
| tests=($(ctest -R ${test_suite} -V -N | grep -E " +Test +#[0-9]+*" | cut -d':' -f2 | awk '{$1=$1};1')) | |
| if [ ${#tests[@]} -eq 0 ]; then | |
| abort "No tests available... check your compilation process..." | |
| fi | |
| popd > /dev/null || exit 1 | |
| # Step 4: Identify Test Command for Debugging | |
| ############################################# | |
| # Select test number | |
| if [ -z $test_number ]; then | |
| # List out available tests | |
| printf "Which test would you like to debug?\n" | |
| id=0 | |
| for s in "${tests[@]}" | |
| do | |
| echo "Test# ${id}" | |
| echo " $s" | |
| ((id++)) | |
| done | |
| # Prompt user which test they wanted to run | |
| printf "\nRun test#? " | |
| read test_number | |
| else | |
| printf "\nUser Already Requested #${test_number}\n" | |
| fi | |
| # Grab all tests commands | |
| pushd "$build_dir" | |
| sIFS=$IFS # Save Initial IFS (Internal Field Separator) | |
| IFS=$'\n' # Change IFS (Internal Field Separator) (So we split ctest output by newline rather than by spaces) | |
| test_args=($(ctest -R ${test_suite} -V -N | grep "Test command" | cut -d':' -f3 | awk '{$1=$1};1' )) # Get test args | |
| IFS=$sIFS # Reset IFS (Internal Field Separator) | |
| popd > /dev/null || exit 1 | |
| # Grab specific test command | |
| single_test_name="${tests[test_number]}" | |
| single_test_command="${test_args[test_number]}" | |
| # Step 5: Execute or GDB Debug | |
| ############################## | |
| printf "${magenta}Running Test #${test_number}: ${single_test_name}${normal}\n" | |
| printf "${cyan}single_test_command: ${single_test_command}${normal}\n" | |
| if [ "$gdb_mode" = "true" ]; then | |
| # Execute debugger | |
| pushd "$repo_root" || exit 1 | |
| eval "gdb --args ${single_test_command}" | |
| popd > /dev/null || exit 1 | |
| else | |
| # Execute Test | |
| pushd "$repo_root" || exit 1 | |
| eval "${single_test_command}" | |
| exit_code=$? | |
| popd > /dev/null || exit 1 | |
| # Print Result | |
| printf "${blue}Ran Test #${test_number}: ${single_test_name}${normal}\n" | |
| printf "${yellow}Command: ${single_test_command}${normal}\n" | |
| if [ $exit_code -eq 0 ]; then | |
| printf "${green}TEST PASS${normal}\n" | |
| else | |
| printf "${red}TEST FAIL${normal}\n" | |
| fi | |
| fi | |
| # Return to the directory from which the user ran the command. | |
| popd > /dev/null || exit 1 | |