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

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

juliehunter commited on Jan 7, 2025

Commit

ba791ca

verified ·

1 Parent(s): 6fe89f0

Update /data-server/models/text/llm/multilang/Lucie-7B/instruct/full_instruct/assistant_only/mix_1/transformers_checkpoints/global_step208/config.json

Browse files

Files changed (1) hide show

config.json +82 -0

config.json ADDED Viewed

	@@ -0,0 +1,82 @@

+{
+  "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"
+}