Text Generation
Transformers
TensorBoard
Safetensors
opt
Generated from Trainer
text-generation-inference
Instructions to use krushnakant27/bertQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krushnakant27/bertQA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="krushnakant27/bertQA", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("krushnakant27/bertQA") model = AutoModelForCausalLM.from_pretrained("krushnakant27/bertQA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use krushnakant27/bertQA with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "krushnakant27/bertQA" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "krushnakant27/bertQA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/krushnakant27/bertQA
- SGLang
How to use krushnakant27/bertQA 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 "krushnakant27/bertQA" \ --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": "krushnakant27/bertQA", "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 "krushnakant27/bertQA" \ --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": "krushnakant27/bertQA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use krushnakant27/bertQA with Docker Model Runner:
docker model run hf.co/krushnakant27/bertQA
End of training
Browse files
README.md
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### Framework versions
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- Transformers 4.
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- Pytorch 2.
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- Datasets 2.19.
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- Tokenizers 0.19.1
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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generation_config.json
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"bos_token_id": 2,
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"transformers_version": "4.
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}
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"bos_token_id": 2,
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"eos_token_id": 2,
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"pad_token_id": 1,
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"transformers_version": "4.41.2"
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}
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runs/Jun06_17-49-26_a461284479d3/events.out.tfevents.1717699763.a461284479d3.831.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:5bfaaccfcdb1ba20ad6e027d4c68bb9dafeacc8788b435ff21bc27deb8e7127a
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size 359
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