Instructions to use DiscoResearch/DiscoLM-70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DiscoResearch/DiscoLM-70b with Transformers:

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

pipe = pipeline("text-generation", model="DiscoResearch/DiscoLM-70b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DiscoResearch/DiscoLM-70b")
model = AutoModelForCausalLM.from_pretrained("DiscoResearch/DiscoLM-70b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DiscoResearch/DiscoLM-70b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DiscoResearch/DiscoLM-70b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DiscoResearch/DiscoLM-70b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DiscoResearch/DiscoLM-70b

SGLang

How to use DiscoResearch/DiscoLM-70b 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 "DiscoResearch/DiscoLM-70b" \
    --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": "DiscoResearch/DiscoLM-70b",
		"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 "DiscoResearch/DiscoLM-70b" \
        --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": "DiscoResearch/DiscoLM-70b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DiscoResearch/DiscoLM-70b with Docker Model Runner:
```
docker model run hf.co/DiscoResearch/DiscoLM-70b
```

bjoernp commited on Dec 5, 2023

Commit

6b3d82d

1 Parent(s): f7a3313

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@@ -164,7 +164,7 @@ DiscoResearch is an aspiring open research community. Disco should be a place wh
 Disco 70b is a [DiscoResearch](https://huggingface.co/DiscoResearch) project and was trained by [Björn Plüster](https://huggingface.co/bjoernp). [Jan Harries](https://huggingface.co/jphme) helped with technical adivce, logistics and the Model Card.
 [AutoMeta](https://huggingface.co/Alignment-Lab-AI) also provided helpful technical advice and rounded up his connections to select a set of high-quality datasets.
-The model was trained with compute provided by [HessianAI](https://hessian.ai/) - many thanks in particular to [Patrick Schramowski](https://huggingface.co/PSaiml) for his support.
 We are standing on the shoulders of giants; many thanks in no particular order to [Laion](https://laion.ai) for LeoLM 70b
 (especially to [Christoph Schuhmann](https://laion.ai) who got us all connected),

 Disco 70b is a [DiscoResearch](https://huggingface.co/DiscoResearch) project and was trained by [Björn Plüster](https://huggingface.co/bjoernp). [Jan Harries](https://huggingface.co/jphme) helped with technical adivce, logistics and the Model Card.
 [AutoMeta](https://huggingface.co/Alignment-Lab-AI) also provided helpful technical advice and rounded up his connections to select a set of high-quality datasets.
+The model was trained with compute provided by [HessianAI](https://hessian.ai/) in collaboration with [LAION](https://laion.ai) - many thanks in particular to [Patrick Schramowski](https://huggingface.co/PSaiml) for his support.
 We are standing on the shoulders of giants; many thanks in no particular order to [Laion](https://laion.ai) for LeoLM 70b
 (especially to [Christoph Schuhmann](https://laion.ai) who got us all connected),