Instructions to use IvanD2002/Stuco_Task_Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IvanD2002/Stuco_Task_Generator with Transformers:

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

pipe = pipeline("text-generation", model="IvanD2002/Stuco_Task_Generator", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("IvanD2002/Stuco_Task_Generator", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("IvanD2002/Stuco_Task_Generator", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use IvanD2002/Stuco_Task_Generator with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IvanD2002/Stuco_Task_Generator"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IvanD2002/Stuco_Task_Generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/IvanD2002/Stuco_Task_Generator

SGLang

How to use IvanD2002/Stuco_Task_Generator 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 "IvanD2002/Stuco_Task_Generator" \
    --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": "IvanD2002/Stuco_Task_Generator",
		"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 "IvanD2002/Stuco_Task_Generator" \
        --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": "IvanD2002/Stuco_Task_Generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use IvanD2002/Stuco_Task_Generator with Docker Model Runner:
```
docker model run hf.co/IvanD2002/Stuco_Task_Generator
```

IvanD2002 commited on Apr 5, 2024

Commit

bc16d30

verified ·

1 Parent(s): e262417

Update config.json

Browse files

Files changed (1) hide show

config.json +2 -20

config.json CHANGED Viewed

@@ -20,32 +20,14 @@
   "hidden_size": 4544,
   "initializer_range": 0.02,
   "layer_norm_epsilon": 1e-05,
-  "max_position_embeddings": 2048,
   "model_type": "falcon",
   "multi_query": true,
   "new_decoder_architecture": false,
   "num_attention_heads": 71,
   "num_hidden_layers": 32,
-  "num_kv_heads": 71,
   "parallel_attn": true,
-  "quantization_config": {
-    "_load_in_4bit": true,
-    "_load_in_8bit": false,
-    "bnb_4bit_compute_dtype": "float32",
-    "bnb_4bit_quant_type": "fp4",
-    "bnb_4bit_use_double_quant": false,
-    "llm_int8_enable_fp32_cpu_offload": false,
-    "llm_int8_has_fp16_weight": false,
-    "llm_int8_skip_modules": null,
-    "llm_int8_threshold": 6.0,
-    "load_in_4bit": true,
-    "load_in_8bit": false,
-    "quant_method": "bitsandbytes"
-  },
-  "rope_scaling": null,
-  "rope_theta": 10000.0,
-  "torch_dtype": "float16",
-  "transformers_version": "4.38.2",
   "use_cache": true,
   "vocab_size": 65024
 }

   "hidden_size": 4544,
   "initializer_range": 0.02,
   "layer_norm_epsilon": 1e-05,
   "model_type": "falcon",
   "multi_query": true,
   "new_decoder_architecture": false,
   "num_attention_heads": 71,
   "num_hidden_layers": 32,
   "parallel_attn": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.27.4",
   "use_cache": true,
   "vocab_size": 65024
 }