Instructions to use UncleanCode/anacondia-70m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use UncleanCode/anacondia-70m with Transformers:

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

pipe = pipeline("text-generation", model="UncleanCode/anacondia-70m")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("UncleanCode/anacondia-70m")
model = AutoModelForCausalLM.from_pretrained("UncleanCode/anacondia-70m")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use UncleanCode/anacondia-70m with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/UncleanCode/anacondia-70m

SGLang

How to use UncleanCode/anacondia-70m 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 "UncleanCode/anacondia-70m" \
    --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": "UncleanCode/anacondia-70m",
		"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 "UncleanCode/anacondia-70m" \
        --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": "UncleanCode/anacondia-70m",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use UncleanCode/anacondia-70m with Docker Model Runner:
```
docker model run hf.co/UncleanCode/anacondia-70m
```

UncleanCode commited on Aug 22, 2023

Commit

fb3eefb

1 Parent(s): 89226f9

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@@ -10,7 +10,7 @@ pipeline_tag: text-generation
 Anacondia-70m is a Pythia-70m-deduped model fine-tuned with QLoRA on [timdettmers/openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco)
 ## Usage
-Anacondia is not intended for any downstream usage and was trained for educational purposes. Please consider more serious models for inference if this doesn't fall into your usage aim.
 ## Training procedure

 Anacondia-70m is a Pythia-70m-deduped model fine-tuned with QLoRA on [timdettmers/openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco)
 ## Usage
+Anacondia is not intended for any downstream usage and was trained for educational purposes. Please fine tune for downstream tasks or consider more serious models for inference if this doesn't fall into your usage aim.
 ## Training procedure