Instructions to use anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g with Transformers:

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

pipe = pipeline("text-generation", model="anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g")
model = AutoModelForCausalLM.from_pretrained("anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g

SGLang

How to use anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g 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 "anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g" \
    --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": "anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g",
		"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 "anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g" \
        --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": "anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g with Docker Model Runner:
```
docker model run hf.co/anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g
```

anon8231489123 commited on Apr 1, 2023

Commit

4ef20dd

1 Parent(s): 2de81a2

added ggml quantization for cuda model

Browse files

Files changed (2) hide show

ggml_README.txt +15 -0
gpt4-x-alpaca-13b-ggml-q4_1-from-gptq-4bit-128g/ggml-model-q4_1.bin +3 -0

ggml_README.txt ADDED Viewed

	@@ -0,0 +1,15 @@

+The model is for: https://github.com/ggerganov/llama.cpp
+Date: 2023-04-01
+ggml model file magic: 0x67676a74 (ggjt in hex)
+ggml model file version: 1
+Torrent contents:
+The fine tune described at https://huggingface.co/chavinlo/gpt4-x-alpaca converted to ggml format from https://huggingface.co/anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g/blob/f267949dcd5a5e6451933cec3d0b5661f4f9c889/gpt-x-alpaca-13b-native-4bit-128g-cuda.pt
+Details about the GPTQ quantization process: https://huggingface.co/anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g/blob/f267949dcd5a5e6451933cec3d0b5661f4f9c889/README.md
+Tools used:
+[1] Conversion to ggml: https://github.com/ggerganov/llama.cpp/blob/3265b102beb7674d010644ca2a1bd30a58f9f6b5/convert.py and [2]
+[2] Added extra tokens: https://huggingface.co/chavinlo/alpaca-13b/blob/464a0bd1ec16f3a7d5295a0035aff87f307e62f1/added_tokens.json
+[3] Migration to the latest llama.cpp model format: https://github.com/ggerganov/llama.cpp/blob/3525899277d2e2bdc8ec3f0e6e40c47251608700/migrate-ggml-2023-03-30-pr613.py

gpt4-x-alpaca-13b-ggml-q4_1-from-gptq-4bit-128g/ggml-model-q4_1.bin ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:d4a640a1ce33009c244a361c6f87733aacbc2bea90e84d3c304a4c8be2bdf22d
+size 10173322368