Instructions to use llmware/slim-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use llmware/slim-sentiment with Transformers:

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

pipe = pipeline("text-generation", model="llmware/slim-sentiment")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("llmware/slim-sentiment")
model = AutoModelForCausalLM.from_pretrained("llmware/slim-sentiment", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use llmware/slim-sentiment with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/llmware/slim-sentiment

SGLang

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

Docker Model Runner
How to use llmware/slim-sentiment with Docker Model Runner:
```
docker model run hf.co/llmware/slim-sentiment
```

doberst commited on Jan 29, 2024

Commit

02dd038

verified ·

1 Parent(s): e2fac82

Update config.json

Browse files

Files changed (1) hide show

config.json +1 -16

config.json CHANGED Viewed

@@ -1,10 +1,5 @@
 {
-  "aib_version": "model_archive_122723_tiny_llama-1.1b-29",
-  "training_dataset": [
-    "aib_label_samples_524s.jsonl"
-  ],
-  "training_timestamp": "Wed Dec 27 17:43:21 2023",
-  "training_comments": "tiny-llama-1.1b-27",
   "vocab_size": 32000,
   "max_position_embeddings": 2048,
   "hidden_size": 2048,
@@ -64,15 +59,6 @@
   "architectures": [
     "LlamaForCausalLM"
   ],
-  "finetuning_task": null,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1"
-  },
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1
-  },
   "tokenizer_class": null,
   "prefix": null,
   "bos_token_id": 1,
@@ -84,6 +70,5 @@
   "problem_type": null,
   "_name_or_path": "TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T",
   "transformers_version": "4.36.1",
-  "model_type": "llama",
   "trained": "custom training"
 }

 {
+  "model_type": "llama",
   "vocab_size": 32000,
   "max_position_embeddings": 2048,
   "hidden_size": 2048,
   "architectures": [
     "LlamaForCausalLM"
   ],
   "tokenizer_class": null,
   "prefix": null,
   "bos_token_id": 1,
   "problem_type": null,
   "_name_or_path": "TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T",
   "transformers_version": "4.36.1",
   "trained": "custom training"
 }