Instructions to use TroyDoesAI/BlackSheep-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TroyDoesAI/BlackSheep-4B with Transformers:

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

pipe = pipeline("text-generation", model="TroyDoesAI/BlackSheep-4B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TroyDoesAI/BlackSheep-4B")
model = AutoModelForCausalLM.from_pretrained("TroyDoesAI/BlackSheep-4B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TroyDoesAI/BlackSheep-4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TroyDoesAI/BlackSheep-4B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TroyDoesAI/BlackSheep-4B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TroyDoesAI/BlackSheep-4B

SGLang

How to use TroyDoesAI/BlackSheep-4B 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 "TroyDoesAI/BlackSheep-4B" \
    --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": "TroyDoesAI/BlackSheep-4B",
		"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 "TroyDoesAI/BlackSheep-4B" \
        --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": "TroyDoesAI/BlackSheep-4B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TroyDoesAI/BlackSheep-4B with Docker Model Runner:
```
docker model run hf.co/TroyDoesAI/BlackSheep-4B
```

BlackSheep-4B / tokenizer_config.json

TroyDoesAI

This monster is rude. :)

3e85f30 verified almost 2 years ago

raw

history blame contribute delete

8.27 kB

	{
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	"added_tokens_decoder": {
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	"32022": {
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	"32023": {
	"content": "<\|meta_start\|>",
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	"32024": {
	"content": "<\|ipynb_marker\|>",
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	"special": true
	},
	"32025": {
	"content": "<\|diff_marker\|>",
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	"normalized": false,
	"rstrip": true,
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	"special": true
	},
	"32026": {
	"content": "<\|ghissue\|>",
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	},
	"32027": {
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	},
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	"content": "<\|disc_sep\|>",
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	"content": "<\|disc_thread\|><\|query\|>",
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	}
	},
	"additional_special_tokens": [
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	],
	"bos_token": "<s>",
	"chat_template": "{{ bos_token }}{% for message in messages %}{{'<\|' + message['role'] + '\|>' + '\n' + message['content'] + '<\|end\|>\n' }}{% endfor %}{% if add_generation_prompt %}{{ '<\|assistant\|>\n' }}{% else %}{{ eos_token }}{% endif %}",
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	"model_max_length": 4096,
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	"padding_side": "left",
	"sp_model_kwargs": {},
	"tokenizer_class": "LlamaTokenizer",
	"unk_token": "<unk>",
	"use_default_system_prompt": false
	}