Instructions to use migueldeguzmandev/Phi-1.5-RLLMv3-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use migueldeguzmandev/Phi-1.5-RLLMv3-2 with Transformers:

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

pipe = pipeline("text-generation", model="migueldeguzmandev/Phi-1.5-RLLMv3-2", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("migueldeguzmandev/Phi-1.5-RLLMv3-2", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("migueldeguzmandev/Phi-1.5-RLLMv3-2", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use migueldeguzmandev/Phi-1.5-RLLMv3-2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "migueldeguzmandev/Phi-1.5-RLLMv3-2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "migueldeguzmandev/Phi-1.5-RLLMv3-2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/migueldeguzmandev/Phi-1.5-RLLMv3-2

SGLang

How to use migueldeguzmandev/Phi-1.5-RLLMv3-2 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 "migueldeguzmandev/Phi-1.5-RLLMv3-2" \
    --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": "migueldeguzmandev/Phi-1.5-RLLMv3-2",
		"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 "migueldeguzmandev/Phi-1.5-RLLMv3-2" \
        --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": "migueldeguzmandev/Phi-1.5-RLLMv3-2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use migueldeguzmandev/Phi-1.5-RLLMv3-2 with Docker Model Runner:
```
docker model run hf.co/migueldeguzmandev/Phi-1.5-RLLMv3-2
```

migueldeguzmandev commited on Feb 17, 2024

Commit

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@@ -1,5 +1,5 @@
-Companion Post: Research Log, RLLMv3 (GPT2-XL, Phi-1.5 and Falcon-RW-1B)
-Main post: BetterDAN, AI Machiavelli & Oppo Jailbreaks vs. SOTA models & GPT2XL_RLLMv3
-Related post: Coherence (and Response Time) Test

+Companion Post: [Research Log, RLLMv3 (GPT2-XL, Phi-1.5 and Falcon-RW-1B)](https://www.lesswrong.com/posts/EiEhYmYsvYCRgCemH/research-log-rllmv3-gpt2-xl-phi-1-5-and-falcon-rw-1b?utm_campaign=post_share&utm_source=link)
+Main post: [BetterDAN, AI Machiavelli & Oppo Jailbreaks vs. SOTA models & GPT2XL_RLLMv3](https://www.lesswrong.com/posts/vZ5fM6FtriyyKbwi9/betterdan-ai-machiavelli-and-oppo-jailbreaks-vs-sota-models?utm_campaign=post_share&utm_source=link)
+Related post: [Coherence (and Response Time) Test](https://docs.google.com/document/d/1D235vN2KwsLIUKCySpKJoDLV7qwYcU-LSSDpFCbMljs/edit?usp=sharing)