Instructions to use Ehraim/SequentialLearnerv13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ehraim/SequentialLearnerv13 with Transformers:

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

pipe = pipeline("text-generation", model="Ehraim/SequentialLearnerv13")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Ehraim/SequentialLearnerv13")
model = AutoModelForCausalLM.from_pretrained("Ehraim/SequentialLearnerv13")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Ehraim/SequentialLearnerv13 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ehraim/SequentialLearnerv13"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ehraim/SequentialLearnerv13",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Ehraim/SequentialLearnerv13

SGLang

How to use Ehraim/SequentialLearnerv13 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 "Ehraim/SequentialLearnerv13" \
    --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": "Ehraim/SequentialLearnerv13",
		"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 "Ehraim/SequentialLearnerv13" \
        --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": "Ehraim/SequentialLearnerv13",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Ehraim/SequentialLearnerv13 with Docker Model Runner:
```
docker model run hf.co/Ehraim/SequentialLearnerv13
```

Ehraim commited on Dec 7, 2023

Commit

de0aac4

1 Parent(s): f536e9d

Update adapter_config.json

Browse files

Files changed (1) hide show

adapter_config.json +0 -3

adapter_config.json CHANGED Viewed

@@ -8,11 +8,8 @@
   "init_lora_weights": true,
   "layers_pattern": null,
   "layers_to_transform": null,
-  "loftq_config": {},
   "lora_alpha": 16,
   "lora_dropout": 0.05,
-  "megatron_config": null,
-  "megatron_core": "megatron.core",
   "modules_to_save": null,
   "peft_type": "LORA",
   "r": 16,

   "init_lora_weights": true,
   "layers_pattern": null,
   "layers_to_transform": null,
   "lora_alpha": 16,
   "lora_dropout": 0.05,
   "modules_to_save": null,
   "peft_type": "LORA",
   "r": 16,