Instructions to use uukuguy/speechless-code-mistral-7b-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use uukuguy/speechless-code-mistral-7b-v1.0 with Transformers:

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

pipe = pipeline("text-generation", model="uukuguy/speechless-code-mistral-7b-v1.0")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("uukuguy/speechless-code-mistral-7b-v1.0")
model = AutoModelForMultimodalLM.from_pretrained("uukuguy/speechless-code-mistral-7b-v1.0")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use uukuguy/speechless-code-mistral-7b-v1.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "uukuguy/speechless-code-mistral-7b-v1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "uukuguy/speechless-code-mistral-7b-v1.0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/uukuguy/speechless-code-mistral-7b-v1.0

SGLang

How to use uukuguy/speechless-code-mistral-7b-v1.0 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 "uukuguy/speechless-code-mistral-7b-v1.0" \
    --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": "uukuguy/speechless-code-mistral-7b-v1.0",
		"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 "uukuguy/speechless-code-mistral-7b-v1.0" \
        --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": "uukuguy/speechless-code-mistral-7b-v1.0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use uukuguy/speechless-code-mistral-7b-v1.0 with Docker Model Runner:
```
docker model run hf.co/uukuguy/speechless-code-mistral-7b-v1.0
```

uukuguy commited on Dec 30, 2023

Commit

1862e0a

1 Parent(s): 43dea8e

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@@ -45,7 +45,18 @@ Total 201,981 samples.
 - TokenBender/python_eval_instruct_51k: “python” in output .40,309 samples
 - Spider: 8,659 samples
 ## HumanEval

 - TokenBender/python_eval_instruct_51k: “python” in output .40,309 samples
 - Spider: 8,659 samples
+## How to Prompt the Model
+This model accepts the Alpaca instruction format.
+For example:
+```
+You are an intelligent programming assistant.
+### Instruction:
+Implement a linked list in C++
+### Response:
+```
 ## HumanEval