Instructions to use chargoddard/MelangeA-70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chargoddard/MelangeA-70b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="chargoddard/MelangeA-70b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("chargoddard/MelangeA-70b") model = AutoModelForCausalLM.from_pretrained("chargoddard/MelangeA-70b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use chargoddard/MelangeA-70b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "chargoddard/MelangeA-70b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "chargoddard/MelangeA-70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/chargoddard/MelangeA-70b
- SGLang
How to use chargoddard/MelangeA-70b 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 "chargoddard/MelangeA-70b" \ --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": "chargoddard/MelangeA-70b", "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 "chargoddard/MelangeA-70b" \ --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": "chargoddard/MelangeA-70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use chargoddard/MelangeA-70b with Docker Model Runner:
docker model run hf.co/chargoddard/MelangeA-70b
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Check out the documentation for more information.
Experimental merge. Details to come if successful.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 55.92 |
| ARC (25-shot) | 71.25 |
| HellaSwag (10-shot) | 87.3 |
| MMLU (5-shot) | 70.56 |
| TruthfulQA (0-shot) | 60.61 |
| Winogrande (5-shot) | 81.53 |
| GSM8K (5-shot) | 5.69 |
| DROP (3-shot) | 14.53 |
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