Text Generation
Transformers
PyTorch
RefinedWeb
falcon-40b
rlhf
falcon
custom_code
text-generation-inference
Instructions to use lightonai/alfred-40b-0723 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lightonai/alfred-40b-0723 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lightonai/alfred-40b-0723", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("lightonai/alfred-40b-0723", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use lightonai/alfred-40b-0723 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lightonai/alfred-40b-0723" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lightonai/alfred-40b-0723", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lightonai/alfred-40b-0723
- SGLang
How to use lightonai/alfred-40b-0723 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 "lightonai/alfred-40b-0723" \ --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": "lightonai/alfred-40b-0723", "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 "lightonai/alfred-40b-0723" \ --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": "lightonai/alfred-40b-0723", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lightonai/alfred-40b-0723 with Docker Model Runner:
docker model run hf.co/lightonai/alfred-40b-0723
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README.md
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### Training Procedure
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`Alfred-40B-0723` was trained on 128 A100 40GB GPUs, using a 3D parallelism strategy (TP=8, PP=4, DP=4) combined with ZeRO.
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#### Preprocessing
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`Alfred-40B-0723` was trained on 128 A100 40GB GPUs, using a 3D parallelism strategy (TP=8, PP=4, DP=4) combined with ZeRO. The value model is initialized from the reward model and does not have any shared parameters with the policy network.
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#### Preprocessing
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