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 Settings
- 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
Upload LlamaForCausalLM
Browse files- config.json +2 -2
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config.json
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{
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"hidden_size": 2048,
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"max_position_embeddings":
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 24,
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"_name_or_path": "llama_1.3b_enko_v230free_4k_300b",
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"architectures": [
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"LlamaForCausalLM"
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],
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"hidden_size": 2048,
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"initializer_range": 0.01,
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"intermediate_size": 5632,
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"max_position_embeddings": 4096,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 24,
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pytorch_model.bin
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