Instructions to use ConeML/coneml-810m-alpha-arithmetic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ConeML/coneml-810m-alpha-arithmetic with Transformers:

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

pipe = pipeline("text-generation", model="ConeML/coneml-810m-alpha-arithmetic")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ConeML/coneml-810m-alpha-arithmetic")
model = AutoModelForCausalLM.from_pretrained("ConeML/coneml-810m-alpha-arithmetic", device_map="auto")
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 Settings

llama.cpp

How to use ConeML/coneml-810m-alpha-arithmetic with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ConeML/coneml-810m-alpha-arithmetic:Q8_0
# Run inference directly in the terminal:
llama cli -hf ConeML/coneml-810m-alpha-arithmetic:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ConeML/coneml-810m-alpha-arithmetic:Q8_0
# Run inference directly in the terminal:
llama cli -hf ConeML/coneml-810m-alpha-arithmetic:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf ConeML/coneml-810m-alpha-arithmetic:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf ConeML/coneml-810m-alpha-arithmetic:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf ConeML/coneml-810m-alpha-arithmetic:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ConeML/coneml-810m-alpha-arithmetic:Q8_0

Use Docker

docker model run hf.co/ConeML/coneml-810m-alpha-arithmetic:Q8_0

LM Studio
Jan

vLLM

How to use ConeML/coneml-810m-alpha-arithmetic with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ConeML/coneml-810m-alpha-arithmetic"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ConeML/coneml-810m-alpha-arithmetic",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ConeML/coneml-810m-alpha-arithmetic:Q8_0

SGLang

How to use ConeML/coneml-810m-alpha-arithmetic 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 "ConeML/coneml-810m-alpha-arithmetic" \
    --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": "ConeML/coneml-810m-alpha-arithmetic",
		"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 "ConeML/coneml-810m-alpha-arithmetic" \
        --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": "ConeML/coneml-810m-alpha-arithmetic",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use ConeML/coneml-810m-alpha-arithmetic with Ollama:
```
ollama run hf.co/ConeML/coneml-810m-alpha-arithmetic:Q8_0
```

Unsloth Studio

How to use ConeML/coneml-810m-alpha-arithmetic with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ConeML/coneml-810m-alpha-arithmetic to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ConeML/coneml-810m-alpha-arithmetic to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ConeML/coneml-810m-alpha-arithmetic to start chatting

Docker Model Runner
How to use ConeML/coneml-810m-alpha-arithmetic with Docker Model Runner:
```
docker model run hf.co/ConeML/coneml-810m-alpha-arithmetic:Q8_0
```

Lemonade

How to use ConeML/coneml-810m-alpha-arithmetic with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ConeML/coneml-810m-alpha-arithmetic:Q8_0

Run and chat with the model

lemonade run user.coneml-810m-alpha-arithmetic-Q8_0

List all available models

lemonade list

Atomic Chat

RandomMountainMan commited on 20 days ago

Commit

e800fc9

verified ·

1 Parent(s): 2175287

Link research releases to commercial model engineering

Browse files

Files changed (2) hide show

README.md +2 -2
SHA256SUMS.txt +1 -1

README.md CHANGED Viewed

@@ -257,13 +257,13 @@ disclosure to be checked against the evidence frozen at release time.
 Public GSM8K and HumanEval rows are not redistributed; only aggregate
 results are published. `SHA256SUMS.txt` covers every shipped file.
-## 10. License and commercial enquiries
 Released for non-commercial use under CC BY-NC 4.0. Commercial use is not
 granted by this release. See `LICENSE.md`.
 For commercial evaluation, model-engineering, or licensing enquiries,
 contact [contact@coneml.com](mailto:contact@coneml.com) or visit
-[coneml.com](https://coneml.com/). Commercial availability does not
 imply that this alpha checkpoint is suitable for an unvalidated
 production workflow.

 Public GSM8K and HumanEval rows are not redistributed; only aggregate
 results are published. `SHA256SUMS.txt` covers every shipped file.
+## 10. Research license and commercial work
 Released for non-commercial use under CC BY-NC 4.0. Commercial use is not
 granted by this release. See `LICENSE.md`.
 For commercial evaluation, model-engineering, or licensing enquiries,
 contact [contact@coneml.com](mailto:contact@coneml.com) or visit
+[ConeML for Organizations](https://coneml.com/organizations/). Commercial availability does not
 imply that this alpha checkpoint is suitable for an unvalidated
 production workflow.

SHA256SUMS.txt CHANGED Viewed

@@ -1,6 +1,6 @@
 846a8e2297580b3c8d57f69a07d88833d370f976010b31d9fc9b93e9a3f04464  LICENSE.md
 1756d02d239f8e8342a1aa513248f9d35b9a5168c77d07619e64a90e20580434  Modelfile
-3e9e8daa45f317778df5d27b315edaa0dcfd6281085665abc7edd27f7c05f11b  README.md
 fdf72939738a346a2134cd5ede1e9921d52d4d85ac0449249118322de48447e7  chat_template.jinja
 147f479696718b5665f3aea3a7ae312cc6850d998246141f6ecbbd7e395bce2d  coneml-810m-alpha-arithmetic-Q8_0.gguf
 5898b62c447961cb7eb60fc538fc9f4b0f0bdda840fda87a861d01c245085c31  coneml-810m-alpha-arithmetic-f16.gguf

 846a8e2297580b3c8d57f69a07d88833d370f976010b31d9fc9b93e9a3f04464  LICENSE.md
 1756d02d239f8e8342a1aa513248f9d35b9a5168c77d07619e64a90e20580434  Modelfile
+3f7f2da2b02a6a2b72fb2244b563a1b74f271e6c0d4fc64527795c3fc3d60042  README.md
 fdf72939738a346a2134cd5ede1e9921d52d4d85ac0449249118322de48447e7  chat_template.jinja
 147f479696718b5665f3aea3a7ae312cc6850d998246141f6ecbbd7e395bce2d  coneml-810m-alpha-arithmetic-Q8_0.gguf
 5898b62c447961cb7eb60fc538fc9f4b0f0bdda840fda87a861d01c245085c31  coneml-810m-alpha-arithmetic-f16.gguf