Instructions to use sometimesanotion/Lamarck-14B-v0.7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sometimesanotion/Lamarck-14B-v0.7 with Transformers:

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

pipe = pipeline("text-generation", model="sometimesanotion/Lamarck-14B-v0.7")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("sometimesanotion/Lamarck-14B-v0.7")
model = AutoModelForCausalLM.from_pretrained("sometimesanotion/Lamarck-14B-v0.7")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use sometimesanotion/Lamarck-14B-v0.7 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sometimesanotion/Lamarck-14B-v0.7"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sometimesanotion/Lamarck-14B-v0.7",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/sometimesanotion/Lamarck-14B-v0.7

SGLang

How to use sometimesanotion/Lamarck-14B-v0.7 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 "sometimesanotion/Lamarck-14B-v0.7" \
    --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": "sometimesanotion/Lamarck-14B-v0.7",
		"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 "sometimesanotion/Lamarck-14B-v0.7" \
        --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": "sometimesanotion/Lamarck-14B-v0.7",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use sometimesanotion/Lamarck-14B-v0.7 with Docker Model Runner:
```
docker model run hf.co/sometimesanotion/Lamarck-14B-v0.7
```

C4ai-command-r-plus Tokenizing?

by Reithan - opened Feb 2, 2025

Discussion

Reithan

Feb 2, 2025

Been alternating between running this model with DeepSeek's tokenizer and Qwen2 tokenizer, both seem to produce strong results - but different ones.

However, I noticed in longer contexts focused on story or RP, Lamarck starts spitting out tokens I've only seen from CohereForAI/c4ai-command-r-plus?

Namely <|CHATBOT_TOKEN|>, and sometimes <act>, which I think is just logical vomit of think->act. But the Cohere token is strange, because I don't see any of that model in any part of the merge history of Lamarck?

Does another model in Lamarck's history use this token?

Reithan

Feb 2, 2025

Nevermind, there was a problem with my UI and some wires got crossed, false alarm. >.>

Reithan changed discussion status to closed Feb 2, 2025

sometimesanotion

Owner Feb 2, 2025

Despite your fix being somewhere else. I'm glad to hear Lamarck is holding up well with different tokenizers. This has been on my radar. Thank you for the feedback!

Reithan

Feb 3, 2025

To clarify, one of my setting got changed from Deekseek-R1 to Command-R, which caused the <|CHATBOT_TOKEN|> to get used - I didn't notice because Lamarck was still giving good output! Except for the in output after which was being hidden by my formatting.

Not sure why <|CHATBOT_TOKEN|> leads to <act> but otherwise that format was working as well.

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