Text Generation
Transformers
PyTorch
English
Chinese
llama
llama2
qwen
causallm
text-generation-inference
Instructions to use CausalLM/14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CausalLM/14B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CausalLM/14B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CausalLM/14B") model = AutoModelForCausalLM.from_pretrained("CausalLM/14B") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use CausalLM/14B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CausalLM/14B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CausalLM/14B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CausalLM/14B
- SGLang
How to use CausalLM/14B 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 "CausalLM/14B" \ --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": "CausalLM/14B", "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 "CausalLM/14B" \ --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": "CausalLM/14B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CausalLM/14B with Docker Model Runner:
docker model run hf.co/CausalLM/14B
Commit 路
5e3a6ee
1
Parent(s): aeb910c
Update README.md
Browse files
README.md
CHANGED
|
@@ -34,6 +34,8 @@ tags:
|
|
| 34 |
|
| 35 |
*Image drawn by GPT-4 DALL路E 3* TL;DR: Perhaps better than all existing models < 70B, in most quantitative evaluations...
|
| 36 |
|
|
|
|
|
|
|
| 37 |
# Read Me:
|
| 38 |
|
| 39 |
Also see [7B Version](https://huggingface.co/CausalLM/7B)
|
|
|
|
| 34 |
|
| 35 |
*Image drawn by GPT-4 DALL路E 3* TL;DR: Perhaps better than all existing models < 70B, in most quantitative evaluations...
|
| 36 |
|
| 37 |
+
**Some problems with llama.cpp on tokenizer, gotta fix soon..**
|
| 38 |
+
|
| 39 |
# Read Me:
|
| 40 |
|
| 41 |
Also see [7B Version](https://huggingface.co/CausalLM/7B)
|