Instructions to use deepparag/DumBot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepparag/DumBot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="deepparag/DumBot") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("deepparag/DumBot") model = AutoModelForCausalLM.from_pretrained("deepparag/DumBot") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use deepparag/DumBot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "deepparag/DumBot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepparag/DumBot", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/deepparag/DumBot
- SGLang
How to use deepparag/DumBot 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 "deepparag/DumBot" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepparag/DumBot", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "deepparag/DumBot" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepparag/DumBot", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use deepparag/DumBot with Docker Model Runner:
docker model run hf.co/deepparag/DumBot
add model
Browse files- config.json +5 -5
- pytorch_model.bin +1 -1
config.json
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"summary_use_proj": true,
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"task_specific_params": {
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"conversational": {
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"max_length": 1000,
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"no_repeat_ngram_size":4,
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"torch_dtype": "float32",
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"summary_use_proj": true,
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"task_specific_params": {
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"conversational": {
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"do_sample": true,
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"max_length": 1000,
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"no_repeat_ngram_size": 4,
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"temperature": 0.9,
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"top_k": 100,
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"top_p": 0.7
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"torch_dtype": "float32",
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pytorch_model.bin
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size 510401385
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