Instructions to use Rijgersberg/GEITje-7B-chat-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Rijgersberg/GEITje-7B-chat-v2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Rijgersberg/GEITje-7B-chat-v2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Rijgersberg/GEITje-7B-chat-v2")
model = AutoModelForCausalLM.from_pretrained("Rijgersberg/GEITje-7B-chat-v2", 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

vLLM

How to use Rijgersberg/GEITje-7B-chat-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Rijgersberg/GEITje-7B-chat-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Rijgersberg/GEITje-7B-chat-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Rijgersberg/GEITje-7B-chat-v2

SGLang

How to use Rijgersberg/GEITje-7B-chat-v2 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 "Rijgersberg/GEITje-7B-chat-v2" \
    --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": "Rijgersberg/GEITje-7B-chat-v2",
		"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 "Rijgersberg/GEITje-7B-chat-v2" \
        --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": "Rijgersberg/GEITje-7B-chat-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Rijgersberg/GEITje-7B-chat-v2 with Docker Model Runner:
```
docker model run hf.co/Rijgersberg/GEITje-7B-chat-v2
```

leaderboard-pr-bot commited on Mar 4, 2024

Commit

ca31669

verified ·

1 Parent(s): 7e45fc9

Adding Evaluation Results

Browse files

This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr

The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.

If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions

Files changed (1) hide show

README.md +20 -7

README.md CHANGED Viewed

@@ -1,19 +1,19 @@
 ---
 license: apache-2.0
-base_model: Rijgersberg/GEITje-7B
 tags:
 - generated_from_trainer
 - GEITje
-model-index:
-- name: GEITje-7B-chat-v2
-  results: []
 datasets:
 - Rijgersberg/no_robots_nl
 - Rijgersberg/ultrachat_10k_nl
 - BramVanroy/dutch_chat_datasets
-language:
-- nl
 pipeline_tag: conversational
 ---
 # GEITje-7B-chat-v2
@@ -99,4 +99,17 @@ The following hyperparameters were used during training:
 - Transformers 4.36.0.dev0
 - Pytorch 2.1.1+cu121
 - Datasets 2.15.0
-- Tokenizers 0.15.0

 ---
+language:
+- nl
 license: apache-2.0
 tags:
 - generated_from_trainer
 - GEITje
 datasets:
 - Rijgersberg/no_robots_nl
 - Rijgersberg/ultrachat_10k_nl
 - BramVanroy/dutch_chat_datasets
+base_model: Rijgersberg/GEITje-7B
 pipeline_tag: conversational
+model-index:
+- name: GEITje-7B-chat-v2
+  results: []
 ---
 # GEITje-7B-chat-v2
 - Transformers 4.36.0.dev0
 - Pytorch 2.1.1+cu121
 - Datasets 2.15.0
+- Tokenizers 0.15.0
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Rijgersberg__GEITje-7B-chat-v2)
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |50.79|
+|AI2 Reasoning Challenge (25-Shot)|50.34|
+|HellaSwag (10-Shot)              |74.13|
+|MMLU (5-Shot)                    |49.00|
+|TruthfulQA (0-shot)              |43.55|
+|Winogrande (5-shot)              |71.51|
+|GSM8k (5-shot)                   |16.22|