Instructions to use deepparag/DumBot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

deepparag commited on Nov 1, 2021

Commit

9494a52

1 Parent(s): 8b07fe7

v2

Browse files

Files changed (4) hide show

config.json +5 -13
pytorch_model.bin +2 -2
tokenizer_config.json +1 -1
training_args.bin +2 -2

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "output-small",
   "activation_function": "gelu_new",
   "architectures": [
     "GPT2LMHeadModel"
@@ -8,6 +8,7 @@
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   "embd_pdrop": 0.1,
   "eos_token_id": 50256,
   "initializer_range": 0.02,
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   "model_type": "gpt2",
@@ -17,10 +18,7 @@
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 }

 {
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   "embd_pdrop": 0.1,
   "eos_token_id": 50256,
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   "n_inner": null,
   "n_layer": 12,
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   "summary_first_dropout": 0.1,
   "summary_proj_to_labels": true,
   "summary_use_proj": true,
   "task_specific_params": {
     "conversational": {
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 }

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