Instructions to use BSC-LT/ALIA-40b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BSC-LT/ALIA-40b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BSC-LT/ALIA-40b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BSC-LT/ALIA-40b") model = AutoModelForCausalLM.from_pretrained("BSC-LT/ALIA-40b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use BSC-LT/ALIA-40b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BSC-LT/ALIA-40b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BSC-LT/ALIA-40b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/BSC-LT/ALIA-40b
- SGLang
How to use BSC-LT/ALIA-40b 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 "BSC-LT/ALIA-40b" \ --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": "BSC-LT/ALIA-40b", "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 "BSC-LT/ALIA-40b" \ --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": "BSC-LT/ALIA-40b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use BSC-LT/ALIA-40b with Docker Model Runner:
docker model run hf.co/BSC-LT/ALIA-40b
v0.9
Browse files- config.json +8 -2
config.json
CHANGED
|
@@ -11,7 +11,7 @@
|
|
| 11 |
"hidden_size": 8192,
|
| 12 |
"initializer_range": 0.02,
|
| 13 |
"intermediate_size": 24576,
|
| 14 |
-
"max_position_embeddings":
|
| 15 |
"mlp_bias": false,
|
| 16 |
"model_type": "llama",
|
| 17 |
"num_attention_heads": 64,
|
|
@@ -19,7 +19,13 @@
|
|
| 19 |
"num_key_value_heads": 8,
|
| 20 |
"pretraining_tp": 1,
|
| 21 |
"rms_norm_eps": 1e-05,
|
| 22 |
-
"rope_scaling":
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 23 |
"rope_theta": 10000.0,
|
| 24 |
"tie_word_embeddings": false,
|
| 25 |
"torch_dtype": "bfloat16",
|
|
|
|
| 11 |
"hidden_size": 8192,
|
| 12 |
"initializer_range": 0.02,
|
| 13 |
"intermediate_size": 24576,
|
| 14 |
+
"max_position_embeddings": 32768,
|
| 15 |
"mlp_bias": false,
|
| 16 |
"model_type": "llama",
|
| 17 |
"num_attention_heads": 64,
|
|
|
|
| 19 |
"num_key_value_heads": 8,
|
| 20 |
"pretraining_tp": 1,
|
| 21 |
"rms_norm_eps": 1e-05,
|
| 22 |
+
"rope_scaling": {
|
| 23 |
+
"factor": 8.0,
|
| 24 |
+
"high_freq_factor": 4.0,
|
| 25 |
+
"low_freq_factor": 1.0,
|
| 26 |
+
"original_max_position_embeddings": 4096,
|
| 27 |
+
"rope_type": "llama3"
|
| 28 |
+
},
|
| 29 |
"rope_theta": 10000.0,
|
| 30 |
"tie_word_embeddings": false,
|
| 31 |
"torch_dtype": "bfloat16",
|