Instructions to use pfnet/plamo-2-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pfnet/plamo-2-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pfnet/plamo-2-1b", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("pfnet/plamo-2-1b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pfnet/plamo-2-1b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pfnet/plamo-2-1b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pfnet/plamo-2-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pfnet/plamo-2-1b
- SGLang
How to use pfnet/plamo-2-1b 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 "pfnet/plamo-2-1b" \ --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": "pfnet/plamo-2-1b", "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 "pfnet/plamo-2-1b" \ --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": "pfnet/plamo-2-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pfnet/plamo-2-1b with Docker Model Runner:
docker model run hf.co/pfnet/plamo-2-1b
Properly propagate `model_inputs` (#14)
Browse files- Properly propagate `model_inputs` (3947136e80ad57d10a80752afe1f2442238750e3)
- modeling_plamo.py +3 -0
modeling_plamo.py
CHANGED
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@@ -1663,6 +1663,9 @@ class Plamo2ForCausalLM(Plamo2PreTrainedModel):
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"position_ids": position_ids,
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"past_key_values": past_key_values,
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"use_cache": kwargs.get("use_cache"),
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"attention_mask": attention_mask,
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"image_features": image_features,
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}
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"position_ids": position_ids,
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"past_key_values": past_key_values,
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"use_cache": kwargs.get("use_cache"),
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+
"output_attentions": kwargs.get("output_attentions"),
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"output_hidden_states": kwargs.get("output_hidden_states"),
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"logits_to_keep": kwargs.get("logits_to_keep"),
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"attention_mask": attention_mask,
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"image_features": image_features,
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}
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