Instructions to use collision-10M/Collision-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use collision-10M/Collision-1B with Transformers:

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

pipe = pipeline("text-generation", model="collision-10M/Collision-1B", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("collision-10M/Collision-1B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use collision-10M/Collision-1B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "collision-10M/Collision-1B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "collision-10M/Collision-1B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/collision-10M/Collision-1B

SGLang

How to use collision-10M/Collision-1B 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 "collision-10M/Collision-1B" \
    --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": "collision-10M/Collision-1B",
		"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 "collision-10M/Collision-1B" \
        --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": "collision-10M/Collision-1B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use collision-10M/Collision-1B with Docker Model Runner:
```
docker model run hf.co/collision-10M/Collision-1B
```

Collision-1B / tokenizer_config.json

collision-10M

Fix AutoTokenizer configuration schema warning and update tokenizer_config.json

e21bcb0 verified about 1 month ago

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233 Bytes

{
  "tokenizer_class": "tokenization_collision.CollisionTokenizer",
  "bos_token": "[BOS]",
  "eos_token": "[EOS]",
  "unk_token": "[UNK]",
  "pad_token": "[PAD]",
  "model_max_length": 1024,
  "clean_up_tokenization_spaces": true
}

	{
	"tokenizer_class": "tokenization_collision.CollisionTokenizer",
	"bos_token": "[BOS]",
	"eos_token": "[EOS]",
	"unk_token": "[UNK]",
	"pad_token": "[PAD]",
	"model_max_length": 1024,
	"clean_up_tokenization_spaces": true
	}