Instructions to use athirdpath/CleverGirl-20b-Blended-v1.1-DARE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use athirdpath/CleverGirl-20b-Blended-v1.1-DARE with Transformers:

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

pipe = pipeline("text-generation", model="athirdpath/CleverGirl-20b-Blended-v1.1-DARE")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("athirdpath/CleverGirl-20b-Blended-v1.1-DARE")
model = AutoModelForCausalLM.from_pretrained("athirdpath/CleverGirl-20b-Blended-v1.1-DARE", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use athirdpath/CleverGirl-20b-Blended-v1.1-DARE with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "athirdpath/CleverGirl-20b-Blended-v1.1-DARE"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "athirdpath/CleverGirl-20b-Blended-v1.1-DARE",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/athirdpath/CleverGirl-20b-Blended-v1.1-DARE

SGLang

How to use athirdpath/CleverGirl-20b-Blended-v1.1-DARE 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 "athirdpath/CleverGirl-20b-Blended-v1.1-DARE" \
    --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": "athirdpath/CleverGirl-20b-Blended-v1.1-DARE",
		"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 "athirdpath/CleverGirl-20b-Blended-v1.1-DARE" \
        --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": "athirdpath/CleverGirl-20b-Blended-v1.1-DARE",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use athirdpath/CleverGirl-20b-Blended-v1.1-DARE with Docker Model Runner:
```
docker model run hf.co/athirdpath/CleverGirl-20b-Blended-v1.1-DARE
```

athirdpath commited on Nov 30, 2023

Commit

02a604c

1 Parent(s): e337740

Update README.md

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@@ -9,6 +9,10 @@ After I put down the joint and [RTFM](https://arxiv.org/pdf/2311.03099.pdf), I h
 By lowering the density, I hit closer to the sweet-spot shown in the paper. Also, I'm using my fixed base model, so hopefully that helps too. Weights are adjusted to make the later layers more aligned with ORCA 2.
 ### Recipe
 merge_method: dare_ties

 By lowering the density, I hit closer to the sweet-spot shown in the paper. Also, I'm using my fixed base model, so hopefully that helps too. Weights are adjusted to make the later layers more aligned with ORCA 2.
+### Results
+I'm quite happy with this model for what it is, a personable and effective assistant. It does infodump a bit, but what genius doesn't? It writes okay erotica and general fiction, it just has an "artifical" tone.
 ### Recipe
 merge_method: dare_ties