Instructions to use wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics") model = AutoModelForCausalLM.from_pretrained("wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics
- SGLang
How to use wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics 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 "wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics" \ --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": "wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics", "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 "wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics" \ --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": "wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics with Docker Model Runner:
docker model run hf.co/wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics
End of training
Browse files- .gitignore +1 -0
- config.json +54 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- runs/Jun09_13-51-19_b5421cba8fd0/1654782687.0954502/events.out.tfevents.1654782687.b5421cba8fd0.79.1 +3 -0
- runs/Jun09_13-51-19_b5421cba8fd0/events.out.tfevents.1654782687.b5421cba8fd0.79.0 +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- training_args.bin +3 -0
- vocab.json +0 -0
.gitignore
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{
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"_name_or_path": "EleutherAI/gpt-neo-125M",
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"activation_function": "gelu_new",
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"architectures": [
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"GPTNeoForCausalLM"
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"attention_dropout": 0,
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"bos_token_id": 50256,
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"embed_dropout": 0,
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"eos_token_id": 50256,
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"gradient_checkpointing": false,
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"layer_norm_epsilon": 1e-05,
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"max_position_embeddings": 2048,
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"model_type": "gpt_neo",
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"num_heads": 12,
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"num_layers": 12,
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"resid_dropout": 0,
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.19.2",
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"use_cache": true,
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"vocab_size": 50257,
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"window_size": 256
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}
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pytorch_model.bin
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{"bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": "<|endoftext|>"}
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{"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "errors": "replace", "model_max_length": 2048, "special_tokens_map_file": null, "name_or_path": "EleutherAI/gpt-neo-125M", "pad_token": null, "add_bos_token": false, "tokenizer_class": "GPT2Tokenizer"}
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vocab.json
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