Instructions to use haoranxu/ALMA-7B-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haoranxu/ALMA-7B-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="haoranxu/ALMA-7B-R", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("haoranxu/ALMA-7B-R") model = AutoModelForCausalLM.from_pretrained("haoranxu/ALMA-7B-R", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use haoranxu/ALMA-7B-R with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "haoranxu/ALMA-7B-R" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "haoranxu/ALMA-7B-R", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/haoranxu/ALMA-7B-R
- SGLang
How to use haoranxu/ALMA-7B-R 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 "haoranxu/ALMA-7B-R" \ --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": "haoranxu/ALMA-7B-R", "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 "haoranxu/ALMA-7B-R" \ --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": "haoranxu/ALMA-7B-R", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use haoranxu/ALMA-7B-R with Docker Model Runner:
docker model run hf.co/haoranxu/ALMA-7B-R
Update README.md
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README.md
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@@ -22,8 +22,6 @@ We release six translation models presented in the paper:
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- ALMA-13B-LoRA
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- **ALMA-13B-R (NEW!)**: Further LoRA fine-tuning upon ALMA-13B-LoRA with contrastive preference optimization (BEST MODEL!).
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*We have also provided the WMT'22 and WMT'23 translation outputs from ALMA-13B-LoRA and ALMA-13B-R in the `outputs` directory. These outputs also includes our outputs of baselines and can be directly accessed and used for subsequent evaluations.*
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Model checkpoints are released at huggingface:
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| Models | Base Model Link | LoRA Link |
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|:-------------:|:---------------:|:---------:|
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- ALMA-13B-LoRA
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- **ALMA-13B-R (NEW!)**: Further LoRA fine-tuning upon ALMA-13B-LoRA with contrastive preference optimization (BEST MODEL!).
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Model checkpoints are released at huggingface:
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| Models | Base Model Link | LoRA Link |
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|:-------------:|:---------------:|:---------:|
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