Instructions to use jesseD/homer-bot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jesseD/homer-bot with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="jesseD/homer-bot")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jesseD/homer-bot")
model = AutoModelForCausalLM.from_pretrained("jesseD/homer-bot", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jesseD/homer-bot with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jesseD/homer-bot"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jesseD/homer-bot",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jesseD/homer-bot

SGLang

How to use jesseD/homer-bot 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 "jesseD/homer-bot" \
    --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": "jesseD/homer-bot",
		"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 "jesseD/homer-bot" \
        --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": "jesseD/homer-bot",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use jesseD/homer-bot with Docker Model Runner:
```
docker model run hf.co/jesseD/homer-bot
```

jesseD commited on Jan 26, 2022

Commit

26fc3b8

1 Parent(s): 8cea54f

add tokenizer

Browse files

Files changed (3) hide show

added_tokens.json +1 -0
special_tokens_map.json +1 -1
tokenizer.json +0 -0

added_tokens.json ADDED Viewed

	@@ -0,0 +1 @@


1	+ {"<\|startoftext\|>": 50258, "<\|pad\|>": 50257}

special_tokens_map.json CHANGED Viewed

@@ -1 +1 @@

- {"bos_token": {"~~content": "~~<|~~endoftext~~|>", "~~single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "~~eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": "<|~~endoftext~~|>"}


1	+ {"bos_token": "<\|startoftext\|>", "eos_token": {"content": "<\|endoftext\|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<\|endoftext\|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": "<\|pad\|>"}

tokenizer.json CHANGED Viewed

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