Instructions to use TheBloke/WizardCoder-Python-7B-V1.0-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheBloke/WizardCoder-Python-7B-V1.0-AWQ with Transformers:

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

pipe = pipeline("text-generation", model="TheBloke/WizardCoder-Python-7B-V1.0-AWQ")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheBloke/WizardCoder-Python-7B-V1.0-AWQ")
model = AutoModelForCausalLM.from_pretrained("TheBloke/WizardCoder-Python-7B-V1.0-AWQ")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TheBloke/WizardCoder-Python-7B-V1.0-AWQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheBloke/WizardCoder-Python-7B-V1.0-AWQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheBloke/WizardCoder-Python-7B-V1.0-AWQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TheBloke/WizardCoder-Python-7B-V1.0-AWQ

SGLang

How to use TheBloke/WizardCoder-Python-7B-V1.0-AWQ 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 "TheBloke/WizardCoder-Python-7B-V1.0-AWQ" \
    --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": "TheBloke/WizardCoder-Python-7B-V1.0-AWQ",
		"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 "TheBloke/WizardCoder-Python-7B-V1.0-AWQ" \
        --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": "TheBloke/WizardCoder-Python-7B-V1.0-AWQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TheBloke/WizardCoder-Python-7B-V1.0-AWQ with Docker Model Runner:
```
docker model run hf.co/TheBloke/WizardCoder-Python-7B-V1.0-AWQ
```

TheBloke commited on Sep 27, 2023

Commit

fd1daf5

1 Parent(s): 3720a18

Update base_model formatting

Browse files

Files changed (1) hide show

README.md +18 -19

README.md CHANGED Viewed

@@ -1,25 +1,13 @@
 ---
-base_model: https://huggingface.co/WizardLM/WizardCoder-Python-7b-V1.0
-inference: false
-library_name: transformers
 license: llama2
 metrics:
 - code_eval
-model-index:
-- name: WizardCoder-Python-34B-V1.0
-  results:
-  - dataset:
-      name: HumanEval
-      type: openai_humaneval
-    metrics:
-    - name: pass@1
-      type: pass@1
-      value: 0.555
-      verified: false
-    task:
-      type: text-generation
 model_creator: WizardLM
-model_name: WizardCoder Python 7B V1.0
 model_type: llama
 prompt_template: 'Below is an instruction that describes a task. Write a response
   that appropriately completes the request.
@@ -34,8 +22,19 @@ prompt_template: 'Below is an instruction that describes a task. Write a respons
   '
 quantized_by: TheBloke
-tags:
-- code
 ---
 <!-- header start -->

 ---
 license: llama2
+library_name: transformers
+tags:
+- code
 metrics:
 - code_eval
+base_model: WizardLM/WizardCoder-Python-7b-V1.0
+inference: false
 model_creator: WizardLM
 model_type: llama
 prompt_template: 'Below is an instruction that describes a task. Write a response
   that appropriately completes the request.
   '
 quantized_by: TheBloke
+model-index:
+- name: WizardCoder-Python-34B-V1.0
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      name: HumanEval
+      type: openai_humaneval
+    metrics:
+    - type: pass@1
+      value: 0.555
+      name: pass@1
+      verified: false
 ---
 <!-- header start -->