Instructions to use psyche/kollama2-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psyche/kollama2-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="psyche/kollama2-7b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("psyche/kollama2-7b") model = AutoModelForCausalLM.from_pretrained("psyche/kollama2-7b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use psyche/kollama2-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "psyche/kollama2-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "psyche/kollama2-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/psyche/kollama2-7b
- SGLang
How to use psyche/kollama2-7b 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 "psyche/kollama2-7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "psyche/kollama2-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "psyche/kollama2-7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "psyche/kollama2-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use psyche/kollama2-7b with Docker Model Runner:
docker model run hf.co/psyche/kollama2-7b
Fine-tunned Llama-2 Model with Korean Corpus
This model is a further trained Llama-2 model on the Korean datasets.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 43.71 |
| ARC (25-shot) | 53.24 |
| HellaSwag (10-shot) | 78.78 |
| MMLU (5-shot) | 42.31 |
| TruthfulQA (0-shot) | 44.56 |
| Winogrande (5-shot) | 73.95 |
| GSM8K (5-shot) | 5.99 |
| DROP (3-shot) | 7.11 |
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