Text Generation
Transformers
PyTorch
TensorBoard
gpt2
Generated from Trainer
text-generation-inference
Instructions to use annakotarba/model_gpt_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annakotarba/model_gpt_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="annakotarba/model_gpt_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("annakotarba/model_gpt_v1") model = AutoModelForCausalLM.from_pretrained("annakotarba/model_gpt_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use annakotarba/model_gpt_v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "annakotarba/model_gpt_v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "annakotarba/model_gpt_v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/annakotarba/model_gpt_v1
- SGLang
How to use annakotarba/model_gpt_v1 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 "annakotarba/model_gpt_v1" \ --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": "annakotarba/model_gpt_v1", "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 "annakotarba/model_gpt_v1" \ --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": "annakotarba/model_gpt_v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use annakotarba/model_gpt_v1 with Docker Model Runner:
docker model run hf.co/annakotarba/model_gpt_v1
Commit ·
ddf14d4
1
Parent(s): eb21928
End of training
Browse files- .gitignore +1 -0
- config.json +39 -0
- generation_config.json +6 -0
- pytorch_model.bin +3 -0
- runs/Apr24_07-38-06_e66e14cf8495/1682321896.4842324/events.out.tfevents.1682321896.e66e14cf8495.779.9 +3 -0
- runs/Apr24_07-38-06_e66e14cf8495/1682321953.7805123/events.out.tfevents.1682321953.e66e14cf8495.779.11 +3 -0
- runs/Apr24_07-38-06_e66e14cf8495/events.out.tfevents.1682321896.e66e14cf8495.779.8 +3 -0
- runs/Apr24_07-38-06_e66e14cf8495/events.out.tfevents.1682321953.e66e14cf8495.779.10 +3 -0
- runs/Apr24_07-43-03_e66e14cf8495/1682322187.6083531/events.out.tfevents.1682322187.e66e14cf8495.779.17 +3 -0
- runs/Apr24_07-43-03_e66e14cf8495/events.out.tfevents.1682322187.e66e14cf8495.779.16 +3 -0
- runs/Apr24_07-43-30_e66e14cf8495/1682322214.8717947/events.out.tfevents.1682322214.e66e14cf8495.779.19 +3 -0
- runs/Apr24_07-43-30_e66e14cf8495/events.out.tfevents.1682322214.e66e14cf8495.779.18 +3 -0
- training_args.bin +3 -0
.gitignore
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config.json
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{
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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"n_head": 12,
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"n_layer": 12,
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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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"torch_dtype": "float32",
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"transformers_version": "4.28.1",
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"use_cache": true,
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"vocab_size": 50257
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}
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generation_config.json
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"bos_token_id": 50256,
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}
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