Instructions to use aerner/lm-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aerner/lm-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aerner/lm-v2")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("aerner/lm-v2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use aerner/lm-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aerner/lm-v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aerner/lm-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aerner/lm-v2
- SGLang
How to use aerner/lm-v2 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 "aerner/lm-v2" \ --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": "aerner/lm-v2", "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 "aerner/lm-v2" \ --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": "aerner/lm-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aerner/lm-v2 with Docker Model Runner:
docker model run hf.co/aerner/lm-v2
Upload OpenLlamaForCausalLM
#4
by tahomatx - opened
- config.json +3 -3
- pytorch_model.bin +2 -2
config.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "/mnt/n/ml/models/aerner/lm-v2/checkpoint-
|
| 3 |
"architectures": [
|
| 4 |
-
"
|
| 5 |
],
|
| 6 |
"attention_dropout_prob": 0.1,
|
| 7 |
"bos_token_id": 1,
|
|
@@ -12,7 +12,7 @@
|
|
| 12 |
"initializer_range": 0.02,
|
| 13 |
"intermediate_size": 11008,
|
| 14 |
"max_position_embeddings": 2048,
|
| 15 |
-
"model_type": "llama",
|
| 16 |
"num_attention_heads": 32,
|
| 17 |
"num_hidden_layers": 8,
|
| 18 |
"pad_token_id": 0,
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "/mnt/n/ml/models/aerner/lm-v2/checkpoint-76200",
|
| 3 |
"architectures": [
|
| 4 |
+
"OpenLlamaForCausalLM"
|
| 5 |
],
|
| 6 |
"attention_dropout_prob": 0.1,
|
| 7 |
"bos_token_id": 1,
|
|
|
|
| 12 |
"initializer_range": 0.02,
|
| 13 |
"intermediate_size": 11008,
|
| 14 |
"max_position_embeddings": 2048,
|
| 15 |
+
"model_type": "open-llama",
|
| 16 |
"num_attention_heads": 32,
|
| 17 |
"num_hidden_layers": 8,
|
| 18 |
"pad_token_id": 0,
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a8c5dd165b8fc67f0aac39e7162adde3a7aae9c039b5a2d92100dfb2fd91d90d
|
| 3 |
+
size 1760272621
|