Instructions to use trl-internal-testing/tiny-OPTForCausalLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/tiny-OPTForCausalLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="trl-internal-testing/tiny-OPTForCausalLM")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("trl-internal-testing/tiny-OPTForCausalLM") model = AutoModelForCausalLM.from_pretrained("trl-internal-testing/tiny-OPTForCausalLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use trl-internal-testing/tiny-OPTForCausalLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "trl-internal-testing/tiny-OPTForCausalLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "trl-internal-testing/tiny-OPTForCausalLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/trl-internal-testing/tiny-OPTForCausalLM
- SGLang
How to use trl-internal-testing/tiny-OPTForCausalLM 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 "trl-internal-testing/tiny-OPTForCausalLM" \ --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": "trl-internal-testing/tiny-OPTForCausalLM", "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 "trl-internal-testing/tiny-OPTForCausalLM" \ --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": "trl-internal-testing/tiny-OPTForCausalLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use trl-internal-testing/tiny-OPTForCausalLM with Docker Model Runner:
docker model run hf.co/trl-internal-testing/tiny-OPTForCausalLM
Commit ·
5347ea9
1
Parent(s): 2f8f691
Upload OPTForCausalLM (#1)
Browse files- Upload OPTForCausalLM (07a883d8d7490f784301c477df63e24b8442bb98)
- config.json +2 -3
- generation_config.json +1 -1
- model.safetensors +2 -2
config.json
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"dtype": "float16",
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"enable_bias": true,
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"layer_norm_elementwise_affine": true,
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"num_hidden_layers": 2,
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 50265,
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"word_embed_proj_dim": 8
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"dtype": "float16",
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"enable_bias": true,
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"eos_token_id": 2,
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"ffn_dim": 32,
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"hidden_size": 8,
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"init_std": 0.02,
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"layer_norm_elementwise_affine": true,
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"layerdrop": 0.0,
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"max_position_embeddings": 2048,
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"num_hidden_layers": 2,
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"num_key_value_heads": 2,
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"pad_token_id": 1,
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"transformers_version": "4.56.2",
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"use_cache": true,
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"vocab_size": 50265,
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"word_embed_proj_dim": 8
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generation_config.json
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"transformers_version": "4.56.2"
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model.safetensors
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