Instructions to use benjamin/gpt2-wechsel-scottish-gaelic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjamin/gpt2-wechsel-scottish-gaelic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="benjamin/gpt2-wechsel-scottish-gaelic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("benjamin/gpt2-wechsel-scottish-gaelic") model = AutoModelForCausalLM.from_pretrained("benjamin/gpt2-wechsel-scottish-gaelic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use benjamin/gpt2-wechsel-scottish-gaelic with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "benjamin/gpt2-wechsel-scottish-gaelic" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "benjamin/gpt2-wechsel-scottish-gaelic", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/benjamin/gpt2-wechsel-scottish-gaelic
- SGLang
How to use benjamin/gpt2-wechsel-scottish-gaelic 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 "benjamin/gpt2-wechsel-scottish-gaelic" \ --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": "benjamin/gpt2-wechsel-scottish-gaelic", "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 "benjamin/gpt2-wechsel-scottish-gaelic" \ --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": "benjamin/gpt2-wechsel-scottish-gaelic", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use benjamin/gpt2-wechsel-scottish-gaelic with Docker Model Runner:
docker model run hf.co/benjamin/gpt2-wechsel-scottish-gaelic
initial commit
Browse files- README.md +0 -3
- config.json +39 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- rng_state_0.pth +3 -0
- rng_state_1.pth +3 -0
- rng_state_2.pth +3 -0
- rng_state_3.pth +3 -0
- rng_state_4.pth +3 -0
- rng_state_5.pth +3 -0
- rng_state_6.pth +3 -0
- rng_state_7.pth +3 -0
- scheduler.pt +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- trainer_state.json +231 -0
- training_args.bin +3 -0
- vocab.json +0 -0
README.md
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license: mit
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config.json
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{
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"_name_or_path": "gpt2",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"embd_pdrop": 0.1,
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"model_type": "gpt2",
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"n_head": 12,
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"n_layer": 12,
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"n_positions": 1024,
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"resid_pdrop": 0.1,
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"summary_activation": null,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"task_specific_params": {
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"text-generation": {
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"do_sample": true,
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"max_length": 50
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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.12.0.dev0",
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"use_cache": true,
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}
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merges.txt
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pytorch_model.bin
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scheduler.pt
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special_tokens_map.json
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{"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}
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tokenizer.json
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tokenizer_config.json
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{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "models/gpt2_scottish_gaelic", "tokenizer_class": "GPT2Tokenizer"}
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trainer_state.json
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{
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training_args.bin
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vocab.json
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