Instructions to use llmware/bling-tiny-llama-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use llmware/bling-tiny-llama-v0 with Transformers:

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

pipe = pipeline("text-generation", model="llmware/bling-tiny-llama-v0")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("llmware/bling-tiny-llama-v0")
model = AutoModelForCausalLM.from_pretrained("llmware/bling-tiny-llama-v0")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use llmware/bling-tiny-llama-v0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "llmware/bling-tiny-llama-v0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "llmware/bling-tiny-llama-v0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/llmware/bling-tiny-llama-v0

SGLang

How to use llmware/bling-tiny-llama-v0 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/bling-tiny-llama-v0" \
    --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/bling-tiny-llama-v0",
		"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/bling-tiny-llama-v0" \
        --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/bling-tiny-llama-v0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use llmware/bling-tiny-llama-v0 with Docker Model Runner:
```
docker model run hf.co/llmware/bling-tiny-llama-v0
```

doberst commited on Dec 29, 2023

Commit

f4d9e55

1 Parent(s): 6f479d1

Update README.md

Browse files

Files changed (1) hide show

README.md +2 -3

README.md CHANGED Viewed

@@ -17,7 +17,7 @@ Evaluated against the benchmark test:   [RAG-Instruct-Benchmark-Tester](https://
 Average of 2 Test Runs with 1 point for correct answer, 0.5 point for partial correct or blank / NF, 0.0 points for incorrect, and -1 points for hallucinations.
 --**Accuracy Score**:  **86.5** correct out of 100
---Not Found Classification:  85.0% (Very Strong)
 --Boolean:  82.50%
 --Math/Logic:  37.50%
 --Complex Questions (1-5):  3
@@ -34,8 +34,7 @@ For test run results (and good indicator of target use cases), please see the fi
 - **Model type:** TinyLlama
 - **Language(s) (NLP):** English
 - **License:** Apache 2.0
-- **Finetuned from model:** TinyLlama-1.1b - 2.5T checkpoint
 ### Direct Use

 Average of 2 Test Runs with 1 point for correct answer, 0.5 point for partial correct or blank / NF, 0.0 points for incorrect, and -1 points for hallucinations.
 --**Accuracy Score**:  **86.5** correct out of 100
+--Not Found Classification:  85.0%
 --Boolean:  82.50%
 --Math/Logic:  37.50%
 --Complex Questions (1-5):  3
 - **Model type:** TinyLlama
 - **Language(s) (NLP):** English
 - **License:** Apache 2.0
+- **Finetuned from model:** [TinyLlama-1.1b - 2.5T checkpoint](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T)
 ### Direct Use