Text Generation
Transformers
Safetensors
Russian
English
alice_ai
custom_code
mixture-of-experts
vllm
Instructions to use ewgenni/AliceAI-Foundation-80B-A3B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ewgenni/AliceAI-Foundation-80B-A3B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ewgenni/AliceAI-Foundation-80B-A3B-Base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ewgenni/AliceAI-Foundation-80B-A3B-Base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ewgenni/AliceAI-Foundation-80B-A3B-Base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ewgenni/AliceAI-Foundation-80B-A3B-Base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ewgenni/AliceAI-Foundation-80B-A3B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ewgenni/AliceAI-Foundation-80B-A3B-Base
- SGLang
How to use ewgenni/AliceAI-Foundation-80B-A3B-Base 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 "ewgenni/AliceAI-Foundation-80B-A3B-Base" \ --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": "ewgenni/AliceAI-Foundation-80B-A3B-Base", "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 "ewgenni/AliceAI-Foundation-80B-A3B-Base" \ --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": "ewgenni/AliceAI-Foundation-80B-A3B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ewgenni/AliceAI-Foundation-80B-A3B-Base with Docker Model Runner:
docker model run hf.co/ewgenni/AliceAI-Foundation-80B-A3B-Base
Download NOTICES from ewgenni/AliceAI-Foundation-80B-A3B-Base: direct link, hf CLI and curl.
- Browser
- Download file 480 Bytes
-
https://huggingface.co/ewgenni/AliceAI-Foundation-80B-A3B-Base/resolve/f5fda8abf8e0d806b69268ccc52565bcecd4558c/NOTICES
- Command line
-
hf download hf://ewgenni/AliceAI-Foundation-80B-A3B-Base@f5fda8abf8e0d806b69268ccc52565bcecd4558c/NOTICES
-
curl -L -o NOTICES https://huggingface.co/ewgenni/AliceAI-Foundation-80B-A3B-Base/resolve/f5fda8abf8e0d806b69268ccc52565bcecd4558c/NOTICES
480 Bytes
| ------------------------------------------------------------------------------- | |
| Export control notice | |
| ------------------------------------------------------------------------------- | |
| It is necessary to comply with the applicable export control laws and | |
| regulations. We declare that we comply with the applicable export control laws | |
| and regulations for the published software, and we expect the users of the | |
| software and the contributors to it to be compliant with them as well. |