Instructions to use jsfs11/testSLERPmerge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jsfs11/testSLERPmerge with Transformers:

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

pipe = pipeline("text-generation", model="jsfs11/testSLERPmerge")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jsfs11/testSLERPmerge")
model = AutoModelForCausalLM.from_pretrained("jsfs11/testSLERPmerge")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jsfs11/testSLERPmerge with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jsfs11/testSLERPmerge"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jsfs11/testSLERPmerge",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jsfs11/testSLERPmerge

SGLang

How to use jsfs11/testSLERPmerge 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 "jsfs11/testSLERPmerge" \
    --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": "jsfs11/testSLERPmerge",
		"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 "jsfs11/testSLERPmerge" \
        --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": "jsfs11/testSLERPmerge",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use jsfs11/testSLERPmerge with Docker Model Runner:
```
docker model run hf.co/jsfs11/testSLERPmerge
```

jsfs11 commited on Mar 7, 2024

Commit

570fdb6

verified ·

1 Parent(s): 30916de

Update README.md

Browse files

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -10,9 +10,9 @@ base_model:
 - BioMistral/BioMistral-7B
 ---
-# NeuralPipe-7B-slerp
-NeuralPipe-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
 * [jsfs11/testmodelformergev1](https://huggingface.co/jsfs11/testmodelformergev1)
 * [BioMistral/BioMistral-7B](https://huggingface.co/BioMistral/BioMistral-7B)
@@ -46,7 +46,7 @@ from transformers import AutoTokenizer
 import transformers
 import torch
-model = "jsfs11/NeuralPipe-7B-slerp"
 messages = [{"role": "user", "content": "What is a large language model?"}]
 tokenizer = AutoTokenizer.from_pretrained(model)

 - BioMistral/BioMistral-7B
 ---
+# testSLERPmerge
+testSLERPmerge is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
 * [jsfs11/testmodelformergev1](https://huggingface.co/jsfs11/testmodelformergev1)
 * [BioMistral/BioMistral-7B](https://huggingface.co/BioMistral/BioMistral-7B)
 import transformers
 import torch
+model = "jsfs11/testSLERPmerge"
 messages = [{"role": "user", "content": "What is a large language model?"}]
 tokenizer = AutoTokenizer.from_pretrained(model)