Instructions to use recogna-nlp/internlm-chatbode-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use recogna-nlp/internlm-chatbode-20b with Transformers:

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

pipe = pipeline("text-generation", model="recogna-nlp/internlm-chatbode-20b", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("recogna-nlp/internlm-chatbode-20b", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use recogna-nlp/internlm-chatbode-20b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "recogna-nlp/internlm-chatbode-20b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "recogna-nlp/internlm-chatbode-20b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/recogna-nlp/internlm-chatbode-20b

SGLang

How to use recogna-nlp/internlm-chatbode-20b 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 "recogna-nlp/internlm-chatbode-20b" \
    --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": "recogna-nlp/internlm-chatbode-20b",
		"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 "recogna-nlp/internlm-chatbode-20b" \
        --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": "recogna-nlp/internlm-chatbode-20b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use recogna-nlp/internlm-chatbode-20b with Docker Model Runner:
```
docker model run hf.co/recogna-nlp/internlm-chatbode-20b
```

recogna commited on Jul 11, 2024

Commit

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@@ -163,7 +163,10 @@ pipeline_tag: text-generation
 # internlm-chatbode-20b
-<!-- Provide a quick summary of what the model is/does. -->
 O InternLm-ChatBode é um modelo de linguagem ajustado para o idioma português, desenvolvido a partir do modelo [InternLM2](https://huggingface.co/internlm/internlm2-chat-20b). Este modelo foi refinado através do processo de fine-tuning utilizando o dataset UltraAlpaca.

 # internlm-chatbode-20b
+<!--- PROJECT LOGO -->
+<p align="center">
+  <img src="https://huggingface.co/recogna-nlp/internlm-chatbode-7b/resolve/main/_1add1e52-f428-4c7c-bab2-3c6958e029fa.jpeg" alt="ChatBode Logo" width="400" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
+</p>
 O InternLm-ChatBode é um modelo de linguagem ajustado para o idioma português, desenvolvido a partir do modelo [InternLM2](https://huggingface.co/internlm/internlm2-chat-20b). Este modelo foi refinado através do processo de fine-tuning utilizando o dataset UltraAlpaca.