Instructions to use codllm/codllm-base-deploy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use codllm/codllm-base-deploy with Transformers:

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

pipe = pipeline("text-generation", model="codllm/codllm-base-deploy")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("codllm/codllm-base-deploy")
model = AutoModelForSeq2SeqLM.from_pretrained("codllm/codllm-base-deploy", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use codllm/codllm-base-deploy with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "codllm/codllm-base-deploy"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "codllm/codllm-base-deploy",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/codllm/codllm-base-deploy

SGLang

How to use codllm/codllm-base-deploy 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 "codllm/codllm-base-deploy" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "codllm/codllm-base-deploy",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "codllm/codllm-base-deploy" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "codllm/codllm-base-deploy",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use codllm/codllm-base-deploy with Docker Model Runner:
```
docker model run hf.co/codllm/codllm-base-deploy
```

NoHaxRelax commited on Aug 30

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@@ -11,7 +11,6 @@ tags:
   - icd
   - historical-demography
   - digital-humanities
-pipeline_tag: text2text-generation
 base_model: google/flan-t5-base
 ---
@@ -28,7 +27,7 @@ The model is highly sensitive to its input shape. Two formats were trained:
 | format | example |
 |---|---|
 | `cod` | `tabes meseraica` |
-| `cod_age_sex` | `cod: stuipen \| age: unknown \| sex: male` |
 Rules that are easy to get wrong:

   - icd
   - historical-demography
   - digital-humanities
 base_model: google/flan-t5-base
 ---
 | format | example |
 |---|---|
 | `cod` | `tabes meseraica` |
+| `cod_age_sex` | `cod: stuipen \\| age: unknown \\| sex: male` |
 Rules that are easy to get wrong: