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 jc3464 - opened Nov 19, 2023

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+2381

-0

Files changed (5) hide show

config.json +35 -0
generation_config.json +10 -0
model-00001-of-00002.safetensors +3 -0
model-00002-of-00002.safetensors +3 -0
model.safetensors.index.json +0 -0

config.json ADDED Viewed

	@@ -0,0 +1,35 @@

+{
+  "_name_or_path": "meta-llama/Llama-2-70b-hf",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 8192,
+  "initializer_range": 0.02,
+  "intermediate_size": 28672,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 80,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "quip_params": {
+    "codebook": "E8P12",
+    "codesz": 8,
+    "idx_dtype": "torch.int16",
+    "lora_rank": 0,
+    "outlier_channel_split": false,
+    "rescale_WH": false
+  },
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.34.0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,10 @@

+{
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "max_length": 4096,
+  "pad_token_id": 0,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.34.0"
+}

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