Instructions to use breadlicker45/museweb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use breadlicker45/museweb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="breadlicker45/museweb")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("breadlicker45/museweb") model = AutoModelForCausalLM.from_pretrained("breadlicker45/museweb") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use breadlicker45/museweb with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "breadlicker45/museweb" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "breadlicker45/museweb", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/breadlicker45/museweb
- SGLang
How to use breadlicker45/museweb 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 "breadlicker45/museweb" \ --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": "breadlicker45/museweb", "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 "breadlicker45/museweb" \ --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": "breadlicker45/museweb", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use breadlicker45/museweb with Docker Model Runner:
docker model run hf.co/breadlicker45/museweb
Commit ·
5f26c0b
1
Parent(s): ca06bdc
Upload 3 files
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
config.json
CHANGED
|
@@ -10,7 +10,7 @@
|
|
| 10 |
"eos_token_id": 50256,
|
| 11 |
"initializer_range": 0.02,
|
| 12 |
"layer_norm_epsilon": 1e-05,
|
| 13 |
-
"line_by_line":
|
| 14 |
"model_type": "gpt2",
|
| 15 |
"n_ctx": 1024,
|
| 16 |
"n_embd": 768,
|
|
|
|
| 10 |
"eos_token_id": 50256,
|
| 11 |
"initializer_range": 0.02,
|
| 12 |
"layer_norm_epsilon": 1e-05,
|
| 13 |
+
"line_by_line": false,
|
| 14 |
"model_type": "gpt2",
|
| 15 |
"n_ctx": 1024,
|
| 16 |
"n_embd": 768,
|
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:c957000ea7f8df65b8cf098b736dc0a8845d7a2ce727b1233b3d73e8241cb4bf
|
| 3 |
+
size 510396521
|