Text Generation
Transformers
Safetensors
Korean
mistral
Generated from Trainer
text-generation-inference
Instructions to use fiveflow/ATOMM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fiveflow/ATOMM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="fiveflow/ATOMM")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("fiveflow/ATOMM") model = AutoModelForCausalLM.from_pretrained("fiveflow/ATOMM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use fiveflow/ATOMM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "fiveflow/ATOMM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fiveflow/ATOMM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/fiveflow/ATOMM
- SGLang
How to use fiveflow/ATOMM 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 "fiveflow/ATOMM" \ --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": "fiveflow/ATOMM", "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 "fiveflow/ATOMM" \ --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": "fiveflow/ATOMM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use fiveflow/ATOMM with Docker Model Runner:
docker model run hf.co/fiveflow/ATOMM
| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| base_model: mistralai/Mistral-7B-Instruct-v0.1 | |
| model-index: | |
| - name: fiveflow/ATOMM-v0.18 | |
| results: [] | |
| language: | |
| - ko | |
| How to use | |
| ```Python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer, TextGenerationPipeline | |
| model_path = 'fiveflow/ATOMM' | |
| tokenizer = AutoTokenizer.from_pretrained(model_path) | |
| model = AutoModelForCausalLM.from_pretrained(model_path, | |
| device_map="auto", | |
| # load_in_4bit=True, | |
| low_cpu_mem_usage=True) | |
| pipe = TextGenerationPipeline(model = model, tokenizer = tokenizer) | |
| ``` |