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

Libraries

How to use ljcamargo/model_url_lora with Transformers:

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

pipe = pipeline("text-generation", model="ljcamargo/model_url_lora")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ljcamargo/model_url_lora", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ljcamargo/model_url_lora with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/ljcamargo/model_url_lora

SGLang

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

Unsloth Studio

How to use ljcamargo/model_url_lora with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ljcamargo/model_url_lora to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ljcamargo/model_url_lora to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ljcamargo/model_url_lora to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="ljcamargo/model_url_lora",
    max_seq_length=2048,
)

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

ljcamargo commited on Oct 22, 2024

Commit

0b32ea2

verified ·

1 Parent(s): 1724eb7

Trained with Unsloth

Browse files

Upload model trained with Unsloth 2x faster

Files changed (2) hide show

README.md +4 -4
adapter_model.safetensors +2 -2

README.md CHANGED Viewed

@@ -1,19 +1,19 @@
 ---
 base_model: unsloth/meta-llama-3.1-8b-bnb-4bit
 language:
 - es
 - top
 license: apache-2.0
 tags:
 - text-generation-inference
 - transformers
 - unsloth
 - llama
 - trl
-pipeline_tag: text2text-generation
-library_name: transformers
-datasets:
-- ljcamargo/tachiwin_translate
 ---
 # Uploaded  model

 ---
 base_model: unsloth/meta-llama-3.1-8b-bnb-4bit
+datasets:
+- ljcamargo/tachiwin_translate
 language:
 - es
 - top
+library_name: transformers
 license: apache-2.0
+pipeline_tag: text2text-generation
 tags:
 - text-generation-inference
 - transformers
 - unsloth
 - llama
 - trl
 ---
 # Uploaded  model

adapter_model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:483e6d4f731f42d3b860c7d9c3a78f2feb951194af15f6e4f4304c45b40d1e16
-size 167832240

 version https://git-lfs.github.com/spec/v1
+oid sha256:60d95b10b6e140a9626a7058d5038528f2ff80148dc4569b881db56052046509
+size 40