Instructions to use OpenLLM-France/Lucie-7B-Instruct-human-data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use OpenLLM-France/Lucie-7B-Instruct-human-data with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="OpenLLM-France/Lucie-7B-Instruct-human-data", filename="Lucie-7B-Instruct-human-data-q4_k_m.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use OpenLLM-France/Lucie-7B-Instruct-human-data with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M # Run inference directly in the terminal: llama-cli -hf OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M # Run inference directly in the terminal: llama-cli -hf OpenLLM-France/Lucie-7B-Instruct-human-data: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 OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf OpenLLM-France/Lucie-7B-Instruct-human-data: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 OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M
Use Docker
docker model run hf.co/OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use OpenLLM-France/Lucie-7B-Instruct-human-data with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenLLM-France/Lucie-7B-Instruct-human-data" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenLLM-France/Lucie-7B-Instruct-human-data", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M
- Ollama
How to use OpenLLM-France/Lucie-7B-Instruct-human-data with Ollama:
ollama run hf.co/OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M
- Unsloth Studio
How to use OpenLLM-France/Lucie-7B-Instruct-human-data 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 OpenLLM-France/Lucie-7B-Instruct-human-data 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 OpenLLM-France/Lucie-7B-Instruct-human-data to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for OpenLLM-France/Lucie-7B-Instruct-human-data to start chatting
- Docker Model Runner
How to use OpenLLM-France/Lucie-7B-Instruct-human-data with Docker Model Runner:
docker model run hf.co/OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M
- Lemonade
How to use OpenLLM-France/Lucie-7B-Instruct-human-data with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull OpenLLM-France/Lucie-7B-Instruct-human-data:Q4_K_M
Run and chat with the model
lemonade run user.Lucie-7B-Instruct-human-data-Q4_K_M
List all available models
lemonade list
Update /data-server/models/text/llm/multilang/Lucie-7B/instruct/full_instruct/assistant_only/mix_1/transformers_checkpoints/global_step208/config.json
ba791ca verified | { | |
| "vocab_size": 65024, | |
| "max_position_embeddings": 4096, | |
| "hidden_size": 4096, | |
| "intermediate_size": 12288, | |
| "num_hidden_layers": 32, | |
| "num_attention_heads": 32, | |
| "num_key_value_heads": 8, | |
| "hidden_act": "silu", | |
| "initializer_range": 0.02, | |
| "rms_norm_eps": 1e-05, | |
| "pretraining_tp": 1, | |
| "use_cache": true, | |
| "rope_theta": 20000000, | |
| "rope_scaling": null, | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "return_dict": true, | |
| "output_hidden_states": false, | |
| "output_attentions": false, | |
| "torchscript": false, | |
| "torch_dtype": "bfloat16", | |
| "use_bfloat16": false, | |
| "tf_legacy_loss": false, | |
| "pruned_heads": {}, | |
| "tie_word_embeddings": false, | |
| "is_encoder_decoder": false, | |
| "is_decoder": false, | |
| "cross_attention_hidden_size": null, | |
| "add_cross_attention": false, | |
| "tie_encoder_decoder": false, | |
| "max_length": 20, | |
| "min_length": 0, | |
| "do_sample": false, | |
| "early_stopping": false, | |
| "num_beams": 1, | |
| "num_beam_groups": 1, | |
| "diversity_penalty": 0.0, | |
| "temperature": 1.0, | |
| "top_k": 50, | |
| "top_p": 1.0, | |
| "typical_p": 1.0, | |
| "repetition_penalty": 1.0, | |
| "length_penalty": 1.0, | |
| "no_repeat_ngram_size": 0, | |
| "encoder_no_repeat_ngram_size": 0, | |
| "bad_words_ids": null, | |
| "num_return_sequences": 1, | |
| "chunk_size_feed_forward": 0, | |
| "output_scores": false, | |
| "return_dict_in_generate": false, | |
| "forced_bos_token_id": null, | |
| "forced_eos_token_id": null, | |
| "remove_invalid_values": false, | |
| "exponential_decay_length_penalty": null, | |
| "suppress_tokens": null, | |
| "begin_suppress_tokens": null, | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "finetuning_task": null, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1" | |
| }, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "tokenizer_class": null, | |
| "prefix": null, | |
| "bos_token_id": 0, | |
| "pad_token_id": 3, | |
| "eos_token_id": 1, | |
| "sep_token_id": null, | |
| "decoder_start_token_id": null, | |
| "task_specific_params": null, | |
| "problem_type": null, | |
| "_name_or_path": "", | |
| "transformers_version": "4.36.1", | |
| "model_type": "llama" | |
| } |