Instructions to use sequelbox/Llama3.1-8B-PlumCode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sequelbox/Llama3.1-8B-PlumCode with Transformers:

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

pipe = pipeline("text-generation", model="sequelbox/Llama3.1-8B-PlumCode")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("sequelbox/Llama3.1-8B-PlumCode")
model = AutoModelForCausalLM.from_pretrained("sequelbox/Llama3.1-8B-PlumCode")
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

vLLM

How to use sequelbox/Llama3.1-8B-PlumCode with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sequelbox/Llama3.1-8B-PlumCode"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sequelbox/Llama3.1-8B-PlumCode",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/sequelbox/Llama3.1-8B-PlumCode

SGLang

How to use sequelbox/Llama3.1-8B-PlumCode 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 "sequelbox/Llama3.1-8B-PlumCode" \
    --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": "sequelbox/Llama3.1-8B-PlumCode",
		"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 "sequelbox/Llama3.1-8B-PlumCode" \
        --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": "sequelbox/Llama3.1-8B-PlumCode",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use sequelbox/Llama3.1-8B-PlumCode with Docker Model Runner:
```
docker model run hf.co/sequelbox/Llama3.1-8B-PlumCode
```

sequelbox commited on Oct 3, 2024

Commit

171cd59

verified ·

1 Parent(s): cf644d0

eval

Browse files

Files changed (1) hide show

README.md +46 -1

README.md CHANGED Viewed

@@ -4,12 +4,57 @@ base_model:
 - ValiantLabs/Llama3.1-8B-Enigma
 - ValiantLabs/Llama3.1-8B-ShiningValiant2
 library_name: transformers
 tags:
 - mergekit
 - merge
 ---
-# plumcode
 This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

 - ValiantLabs/Llama3.1-8B-Enigma
 - ValiantLabs/Llama3.1-8B-ShiningValiant2
 library_name: transformers
+model-index:
+- name: Llama3.1-8B-PlumCode
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-Shot)
+      type: Winogrande
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 73.16
+      name: acc
 tags:
 - mergekit
 - merge
+- shining-valiant
+- shining-valiant-2
+- enigma
+- plum
+- plumcode
+- code
+- valiant
+- valiant-labs
+- llama
+- llama-3.1
+- llama-3.1-instruct
+- llama-3.1-instruct-8b
+- llama-3
+- llama-3-instruct
+- llama-3-instruct-8b
+- 8b
+- code
+- code-instruct
+- python
+- science
+- physics
+- biology
+- chemistry
+- compsci
+- computer-science
+- engineering
+- technical
+- conversational
+- chat
+- instruct
 ---
+# PlumCode
 This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).