Text Generation
Transformers
PyTorch
Safetensors
English
Korean
llama
causal-lm
42dot_llm
text-generation-inference
Instructions to use 42dot/42dot_LLM-PLM-1.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 42dot/42dot_LLM-PLM-1.3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="42dot/42dot_LLM-PLM-1.3B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("42dot/42dot_LLM-PLM-1.3B") model = AutoModelForCausalLM.from_pretrained("42dot/42dot_LLM-PLM-1.3B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use 42dot/42dot_LLM-PLM-1.3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "42dot/42dot_LLM-PLM-1.3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "42dot/42dot_LLM-PLM-1.3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/42dot/42dot_LLM-PLM-1.3B
- SGLang
How to use 42dot/42dot_LLM-PLM-1.3B 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 "42dot/42dot_LLM-PLM-1.3B" \ --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": "42dot/42dot_LLM-PLM-1.3B", "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 "42dot/42dot_LLM-PLM-1.3B" \ --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": "42dot/42dot_LLM-PLM-1.3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use 42dot/42dot_LLM-PLM-1.3B with Docker Model Runner:
docker model run hf.co/42dot/42dot_LLM-PLM-1.3B
Update README.md
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README.md
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#### Korean (KOBEST)
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|Tasks / Macro-F1|[KoGPT2](https://github.com/SKT-AI/KoGPT2) <br>1.2B|[Polyglot-Ko](https://github.com/EleutherAI/polyglot) <br>1.3B|[XGLM](https://huggingface.co/facebook/xglm-1.7B) <br>1.7B|[PolyLM](https://huggingface.co/DAMO-NLP-MT/polylm-1.7b) <br>1.7B|42dot-PLM <br>1.3B ko-en|
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#### English
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| Tasks / Metric | [MPT](https://huggingface.co/mosaicml/mpt-1b-redpajama-200b) <br>1B | [OPT](https://huggingface.co/facebook/opt-1.3b) <br>1.3B | XGLM <br>1.7B | PolyLM <br>1.7B | 42dot-PLM <br>1.3B ko-en |
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#### Korean (KOBEST)
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<img src="assets/plm_benchmark_ko.png" width="90%" height="90%"/>
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</figure>
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|Tasks / Macro-F1|[KoGPT2](https://github.com/SKT-AI/KoGPT2) <br>1.2B|[Polyglot-Ko](https://github.com/EleutherAI/polyglot) <br>1.3B|[XGLM](https://huggingface.co/facebook/xglm-1.7B) <br>1.7B|[PolyLM](https://huggingface.co/DAMO-NLP-MT/polylm-1.7b) <br>1.7B|42dot-PLM <br>1.3B ko-en|
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#### English
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<figure align="center">
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<img src="assets/plm_benchmark_en.png" width="90%" height="90%"/>
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</figure>
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| Tasks / Metric | [MPT](https://huggingface.co/mosaicml/mpt-1b-redpajama-200b) <br>1B | [OPT](https://huggingface.co/facebook/opt-1.3b) <br>1.3B | XGLM <br>1.7B | PolyLM <br>1.7B | 42dot-PLM <br>1.3B ko-en |
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