Instructions to use gghfez/Mistral-Small-24B-Base-2501 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gghfez/Mistral-Small-24B-Base-2501 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="gghfez/Mistral-Small-24B-Base-2501")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("gghfez/Mistral-Small-24B-Base-2501") model = AutoModelForCausalLM.from_pretrained("gghfez/Mistral-Small-24B-Base-2501", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use gghfez/Mistral-Small-24B-Base-2501 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gghfez/Mistral-Small-24B-Base-2501" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gghfez/Mistral-Small-24B-Base-2501", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/gghfez/Mistral-Small-24B-Base-2501
- SGLang
How to use gghfez/Mistral-Small-24B-Base-2501 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 "gghfez/Mistral-Small-24B-Base-2501" \ --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": "gghfez/Mistral-Small-24B-Base-2501", "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 "gghfez/Mistral-Small-24B-Base-2501" \ --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": "gghfez/Mistral-Small-24B-Base-2501", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use gghfez/Mistral-Small-24B-Base-2501 with Docker Model Runner:
docker model run hf.co/gghfez/Mistral-Small-24B-Base-2501
| { | |
| "dim": 5120, | |
| "n_layers": 40, | |
| "head_dim": 128, | |
| "hidden_dim": 32768, | |
| "n_heads": 32, | |
| "n_kv_heads": 8, | |
| "norm_eps": 1e-05, | |
| "vocab_size": 131072, | |
| "rope_theta": 100000000.0, | |
| "max_seq_len": 32768 | |
| } | |