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

Libraries

How to use refactai/codify_medium_multi with Transformers:

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

pipe = pipeline("text-generation", model="refactai/codify_medium_multi", trust_remote_code=True)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("refactai/codify_medium_multi", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use refactai/codify_medium_multi with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/refactai/codify_medium_multi

SGLang

How to use refactai/codify_medium_multi 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 "refactai/codify_medium_multi" \
    --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": "refactai/codify_medium_multi",
		"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 "refactai/codify_medium_multi" \
        --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": "refactai/codify_medium_multi",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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

smallcloudteam commited on Dec 23, 2022

Commit

6ff24a1

1 Parent(s): ae6835d

Upload tokenizer

Browse files

Files changed (2) hide show

tokenizer.json +11 -1
tokenizer_config.json +2 -0

tokenizer.json CHANGED Viewed

@@ -2,7 +2,17 @@
   "version": "1.0",
   "truncation": null,
   "padding": null,
-  "added_tokens": [],
   "normalizer": null,
   "pre_tokenizer": {
     "type": "ByteLevel",

   "version": "1.0",
   "truncation": null,
   "padding": null,
+  "added_tokens": [
+    {
+      "id": 50256,
+      "content": "<|endoftext|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    }
+  ],
   "normalizer": null,
   "pre_tokenizer": {
     "type": "ByteLevel",

tokenizer_config.json CHANGED Viewed

@@ -2,6 +2,8 @@
   "add_prefix_space": false,
   "bos_token": "<|endoftext|>",
   "eos_token": "<|endoftext|>",
   "tokenizer_class": "CodifyTokenizer",
   "unk_token": "<|endoftext|>"
 }

   "add_prefix_space": false,
   "bos_token": "<|endoftext|>",
   "eos_token": "<|endoftext|>",
+  "name_or_path": "smallcloudai/codify_medium_multi",
+  "special_tokens_map_file": "/home/user/.cache/huggingface/hub/models--smallcloudai--codify_medium_multi/snapshots/ae6835df6784621072944fcc3403ca89f1308f96/special_tokens_map.json",
   "tokenizer_class": "CodifyTokenizer",
   "unk_token": "<|endoftext|>"
 }