Instructions to use GenerTeam/GENERator-v2-prokaryote-1.2b-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use GenerTeam/GENERator-v2-prokaryote-1.2b-base with Transformers:

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

pipe = pipeline("text-generation", model="GenerTeam/GENERator-v2-prokaryote-1.2b-base", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("GenerTeam/GENERator-v2-prokaryote-1.2b-base", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("GenerTeam/GENERator-v2-prokaryote-1.2b-base", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use GenerTeam/GENERator-v2-prokaryote-1.2b-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GenerTeam/GENERator-v2-prokaryote-1.2b-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GenerTeam/GENERator-v2-prokaryote-1.2b-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/GenerTeam/GENERator-v2-prokaryote-1.2b-base

SGLang

How to use GenerTeam/GENERator-v2-prokaryote-1.2b-base 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 "GenerTeam/GENERator-v2-prokaryote-1.2b-base" \
    --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": "GenerTeam/GENERator-v2-prokaryote-1.2b-base",
		"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 "GenerTeam/GENERator-v2-prokaryote-1.2b-base" \
        --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": "GenerTeam/GENERator-v2-prokaryote-1.2b-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use GenerTeam/GENERator-v2-prokaryote-1.2b-base with Docker Model Runner:
```
docker model run hf.co/GenerTeam/GENERator-v2-prokaryote-1.2b-base
```

GenerTeam commited on 26 days ago

Commit

2f4e6a1

verified ·

1 Parent(s): ba976af

Update config.json

Browse files

Files changed (1) hide show

config.json +5 -2

config.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "architectures": [
-    "LlamaForCausalLM"
   ],
   "attention_bias": false,
   "attention_dropout": 0.0,
@@ -24,5 +24,8 @@
   "torch_dtype": "float32",
   "transformers_version": "4.44.0",
   "use_cache": true,
-  "vocab_size": 4128
 }

 {
   "architectures": [
+    "GENERatorForCausalLM"
   ],
   "attention_bias": false,
   "attention_dropout": 0.0,
   "torch_dtype": "float32",
   "transformers_version": "4.44.0",
   "use_cache": true,
+  "vocab_size": 4128,
+  "auto_map": {
+    "AutoModelForCausalLM": "modeling_generator.GENERatorForCausalLM"
+  }
 }