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

Libraries

How to use brain-lab/Llama-2-70b-QuIP-HARP-2Bit with Transformers:

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

pipe = pipeline("text-generation", model="brain-lab/Llama-2-70b-QuIP-HARP-2Bit")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("brain-lab/Llama-2-70b-QuIP-HARP-2Bit")
model = AutoModelForCausalLM.from_pretrained("brain-lab/Llama-2-70b-QuIP-HARP-2Bit", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use brain-lab/Llama-2-70b-QuIP-HARP-2Bit with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/brain-lab/Llama-2-70b-QuIP-HARP-2Bit

SGLang

How to use brain-lab/Llama-2-70b-QuIP-HARP-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 "brain-lab/Llama-2-70b-QuIP-HARP-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": "brain-lab/Llama-2-70b-QuIP-HARP-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 "brain-lab/Llama-2-70b-QuIP-HARP-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": "brain-lab/Llama-2-70b-QuIP-HARP-2Bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use brain-lab/Llama-2-70b-QuIP-HARP-2Bit with Docker Model Runner:
```
docker model run hf.co/brain-lab/Llama-2-70b-QuIP-HARP-2Bit
```

Threeteck commited on 6 days ago

Commit

2da1685

verified ·

1 Parent(s): b03f9ec

Upload folder using huggingface_hub

Browse files

Files changed (7) hide show

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+{
+  "_name_or_path": "meta-llama/Llama-2-70b-hf",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 8192,
+  "initializer_range": 0.02,
+  "intermediate_size": 28672,
+  "max_position_embeddings": 4096,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 80,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "quip_params": {
+    "codebook": "E8P12",
+    "codebook_version": 1,
+    "codesz": 8,
+    "harp": {
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+      "early_stop_window": 0,
+      "fixed_mixer": "had_or_qr",
+      "grad_clip": null,
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+      "hbd_lambda": 0.1,
+      "kron_fallback": false,
+      "lr_u": 0.03,
+      "lr_v": 0.03,
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+      "steps": 1200,
+      "strategy": "proxy",
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+      "theta_init_scale": 0.0,
+      "use_givens_b2": false
+    },
+    "idx_dtype": "torch.int64",
+    "incoh_mode": "harp",
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+    "model_version": 1,
+    "packsz": 4,
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+  "torch_dtype": "float16",
+  "transformers_version": "4.45.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

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+  "pad_token_id": 0,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.45.2"
+}

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