Instructions to use ibivibiv/megamarcoroni-120b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ibivibiv/megamarcoroni-120b with Transformers:

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

pipe = pipeline("text-generation", model="ibivibiv/megamarcoroni-120b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ibivibiv/megamarcoroni-120b")
model = AutoModelForCausalLM.from_pretrained("ibivibiv/megamarcoroni-120b")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ibivibiv/megamarcoroni-120b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ibivibiv/megamarcoroni-120b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ibivibiv/megamarcoroni-120b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ibivibiv/megamarcoroni-120b

SGLang

How to use ibivibiv/megamarcoroni-120b 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 "ibivibiv/megamarcoroni-120b" \
    --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": "ibivibiv/megamarcoroni-120b",
		"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 "ibivibiv/megamarcoroni-120b" \
        --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": "ibivibiv/megamarcoroni-120b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ibivibiv/megamarcoroni-120b with Docker Model Runner:
```
docker model run hf.co/ibivibiv/megamarcoroni-120b
```

ibivibiv commited on Feb 23, 2024

Commit

db2d537

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Update README.md

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@@ -1,11 +1,13 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
@@ -196,6 +198,4 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 ## Model Card Contact
-[More Information Needed]

 ---
 library_name: transformers
+license: apache-2.0
+language:
+- en
 ---
+# Model Card for Mega Marcoroni 120B
+The original got removed and was one of my favorite models.  This one is exactly what it says it is.  2x70B Marcoroni FTW!!!! If you know?  You know!  I'm submitting this for evaluation out of curiousity.  Lets see how it does.
 ## Model Card Contact
+[More Information Needed]