Instructions to use normalcomputing/extended-mind-llama-2-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use normalcomputing/extended-mind-llama-2-7b with Transformers:

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

pipe = pipeline("text-generation", model="normalcomputing/extended-mind-llama-2-7b", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("normalcomputing/extended-mind-llama-2-7b", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use normalcomputing/extended-mind-llama-2-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "normalcomputing/extended-mind-llama-2-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "normalcomputing/extended-mind-llama-2-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/normalcomputing/extended-mind-llama-2-7b

SGLang

How to use normalcomputing/extended-mind-llama-2-7b 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 "normalcomputing/extended-mind-llama-2-7b" \
    --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": "normalcomputing/extended-mind-llama-2-7b",
		"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 "normalcomputing/extended-mind-llama-2-7b" \
        --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": "normalcomputing/extended-mind-llama-2-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use normalcomputing/extended-mind-llama-2-7b with Docker Model Runner:
```
docker model run hf.co/normalcomputing/extended-mind-llama-2-7b
```

phoebeklett commited on Jan 27, 2024

Commit

87c923c

verified ·

1 Parent(s): d1edf41

Update config.json

Browse files

Files changed (1) hide show

config.json +6 -2

config.json CHANGED Viewed

@@ -3,6 +3,10 @@
   "architectures": [
     "ExtendedLlamaForCausalLM"
   ],
   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 1,
@@ -12,7 +16,7 @@
   "initializer_range": 0.02,
   "intermediate_size": 11008,
   "mask_by_sim": true,
-  "max_position_embeddings": 4096,
   "memory_device": "cpu",
   "memory_type": "manual",
   "model_type": "extended-llama",
@@ -21,7 +25,7 @@
   "num_key_value_heads": 32,
   "pad_token_id": 0,
   "pretraining_tp": 1,
-  "rms_norm_eps": 1e-05,
   "rope_scaling": null,
   "rope_theta": 10000.0,
   "sim_threshold": 0.25,

   "architectures": [
     "ExtendedLlamaForCausalLM"
   ],
+  "auto_map": {
+    "AutoConfig": "configuration_llama.ExtendedLlamaConfig",
+    "AutoModelForCausalLM": "modeling_llama.ExtendedLlamaForCausalLM"
+  },
   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 1,
   "initializer_range": 0.02,
   "intermediate_size": 11008,
   "mask_by_sim": true,
+  "max_position_embeddings": 2048,
   "memory_device": "cpu",
   "memory_type": "manual",
   "model_type": "extended-llama",
   "num_key_value_heads": 32,
   "pad_token_id": 0,
   "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
   "rope_scaling": null,
   "rope_theta": 10000.0,
   "sim_threshold": 0.25,