Text Generation
Transformers
PyTorch
Norwegian
Norwegian Bokmål
Norwegian Nynorsk
text2text-generation
T5
NorT5
Norwegian
encoder-decoder
custom_code
Instructions to use ltg/nort5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltg/nort5-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ltg/nort5-small", trust_remote_code=True)# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("ltg/nort5-small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ltg/nort5-small with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ltg/nort5-small" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ltg/nort5-small", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ltg/nort5-small
- SGLang
How to use ltg/nort5-small 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 "ltg/nort5-small" \ --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": "ltg/nort5-small", "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 "ltg/nort5-small" \ --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": "ltg/nort5-small", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ltg/nort5-small with Docker Model Runner:
docker model run hf.co/ltg/nort5-small
Update modeling_nort5.py
Browse files- modeling_nort5.py +1 -1
modeling_nort5.py
CHANGED
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@@ -405,7 +405,7 @@ class NorT5Model(NorT5PreTrainedModel):
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def get_decoder_output(
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self, target_ids, encoder_output, attention_mask
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):
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-
batch_size, seq_length =
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device = target_ids.device
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if attention_mask is None:
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def get_decoder_output(
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self, target_ids, encoder_output, attention_mask
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):
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+
batch_size, seq_length, _ = encoder_output.shape
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device = target_ids.device
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if attention_mask is None:
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