Instructions to use girish00/ConicAI_LLM_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use girish00/ConicAI_LLM_model with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-0.5B-Instruct")
model = PeftModel.from_pretrained(base_model, "girish00/ConicAI_LLM_model")

Transformers

How to use girish00/ConicAI_LLM_model with Transformers:

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

pipe = pipeline("text-generation", model="girish00/ConicAI_LLM_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("girish00/ConicAI_LLM_model")
model = AutoModelForMultimodalLM.from_pretrained("girish00/ConicAI_LLM_model")
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

vLLM

How to use girish00/ConicAI_LLM_model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "girish00/ConicAI_LLM_model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "girish00/ConicAI_LLM_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/girish00/ConicAI_LLM_model

SGLang

How to use girish00/ConicAI_LLM_model 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 "girish00/ConicAI_LLM_model" \
    --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": "girish00/ConicAI_LLM_model",
		"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 "girish00/ConicAI_LLM_model" \
        --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": "girish00/ConicAI_LLM_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use girish00/ConicAI_LLM_model with Docker Model Runner:
```
docker model run hf.co/girish00/ConicAI_LLM_model
```

girish00 commited on Apr 19

Commit

7e079b1

verified ·

1 Parent(s): 0a19b76

clean cloud unavailable error

Browse files

Files changed (1) hide show

infer_cloud.py +20 -1

infer_cloud.py CHANGED Viewed

@@ -176,4 +176,23 @@ def main():
 if __name__ == "__main__":
-    main()

 if __name__ == "__main__":
+    try:
+        main()
+    except RuntimeError as exc:
+        print(
+            json.dumps(
+                {
+                    "error": "Hugging Face cloud inference is unavailable for this model repo.",
+                    "reason": str(exc),
+                    "cloud_available": False,
+                    "hint": (
+                        "Use the default local fallback, deploy a Hugging Face Dedicated "
+                        "Inference Endpoint, or run the model on a cloud VM."
+                    ),
+                },
+                indent=2,
+                ensure_ascii=False,
+            ),
+            file=sys.stderr,
+        )
+        sys.exit(1)