Instructions to use relaxml/Llama-2-70b-E8P-2Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use relaxml/Llama-2-70b-E8P-2Bit with Transformers:

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

pipe = pipeline("text-generation", model="relaxml/Llama-2-70b-E8P-2Bit")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("relaxml/Llama-2-70b-E8P-2Bit")
model = AutoModelForCausalLM.from_pretrained("relaxml/Llama-2-70b-E8P-2Bit")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use relaxml/Llama-2-70b-E8P-2Bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "relaxml/Llama-2-70b-E8P-2Bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "relaxml/Llama-2-70b-E8P-2Bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/relaxml/Llama-2-70b-E8P-2Bit

SGLang

How to use relaxml/Llama-2-70b-E8P-2Bit 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 "relaxml/Llama-2-70b-E8P-2Bit" \
    --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": "relaxml/Llama-2-70b-E8P-2Bit",
		"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 "relaxml/Llama-2-70b-E8P-2Bit" \
        --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": "relaxml/Llama-2-70b-E8P-2Bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use relaxml/Llama-2-70b-E8P-2Bit with Docker Model Runner:
```
docker model run hf.co/relaxml/Llama-2-70b-E8P-2Bit
```

Upload folder using huggingface_hub

by at676 - opened Feb 8, 2024

base: refs/heads/main

←

from: refs/pr/4

Discussion Files changed

+1940

-1926

Files changed (7) hide show

config.json +4 -2
generation_config.json +1 -1
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model-00002-of-00004.safetensors +3 -0
model-00003-of-00004.safetensors +3 -0
model-00004-of-00004.safetensors +3 -0
model.safetensors.index.json +0 -0

config.json CHANGED Viewed

@@ -4,6 +4,7 @@
     "LlamaForCausalLM"
   ],
   "attention_bias": false,
   "bos_token_id": 1,
   "eos_token_id": 2,
   "hidden_act": "silu",
@@ -26,14 +27,15 @@
     "model_version": 1,
     "outlier_channel_split": false,
     "packsz": 4,
-    "rescale_WH": false
   },
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   "torch_dtype": "float16",
-  "transformers_version": "4.34.0",
   "use_cache": true,
   "vocab_size": 32000
 }

     "LlamaForCausalLM"
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   "eos_token_id": 2,
   "hidden_act": "silu",
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   "torch_dtype": "float16",
+  "transformers_version": "4.36.2",
   "use_cache": true,
   "vocab_size": 32000
 }

generation_config.json CHANGED Viewed

@@ -6,5 +6,5 @@
   "pad_token_id": 0,
   "temperature": 0.6,
   "top_p": 0.9,
-  "transformers_version": "4.34.0"
 }

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