Instructions to use legesher/language-decoded-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use legesher/language-decoded-lora with Transformers:

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

pipe = pipeline("text-generation", model="legesher/language-decoded-lora")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("legesher/language-decoded-lora", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use legesher/language-decoded-lora with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/legesher/language-decoded-lora

SGLang

How to use legesher/language-decoded-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 "legesher/language-decoded-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": "legesher/language-decoded-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 "legesher/language-decoded-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": "legesher/language-decoded-lora",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Unsloth Studio

How to use legesher/language-decoded-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 legesher/language-decoded-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 legesher/language-decoded-lora to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for legesher/language-decoded-lora to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="legesher/language-decoded-lora",
    max_seq_length=2048,
)

Docker Model Runner
How to use legesher/language-decoded-lora with Docker Model Runner:
```
docker model run hf.co/legesher/language-decoded-lora
```

language-decoded-lora / README.md

Commit History

docs: delineate Phase 2 (Stack v1) vs Phase 3 (Stack v2-dedup) adapters

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madiedgar commited on May 31

docs: add arxiv: tags for paper bibliography anchors (#11)

aa01d9a

madiedgar commited on May 31

docs(readme): align with canonical source-of-truth (cond-5 adapters, source-file control, refined extractor) (#10)

06802f3

madiedgar commited on May 31

docs(readme): cond-5 refined-extractor banner + Phase 3 staleness fixes (#9)

625893e

madiedgar commited on May 31

docs: add condition-1-en-32k to Model Structure table (#7)

6ac3acd

madiedgar commited on Mar 31

docs: fix license to Apache 2.0, add hyperparameters + limitations, update citations (#3)

689d1ea

madiedgar commited on Mar 31

Upload model trained with Unsloth

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Rashik24 commited on Mar 22

Update model card: fix conditions, base model, benchmarks, languages (#1)

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madiedgar commited on Mar 20

init: create README.md

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initial commit

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Commit History

docs: delineate Phase 2 (Stack v1) vs Phase 3 (Stack v2-dedup) adapters 5a8663a verified

docs: add arxiv: tags for paper bibliography anchors (#11) aa01d9a

docs(readme): align with canonical source-of-truth (cond-5 adapters, source-file control, refined extractor) (#10) 06802f3

docs(readme): cond-5 refined-extractor banner + Phase 3 staleness fixes (#9) 625893e

docs: add condition-1-en-32k to Model Structure table (#7) 6ac3acd

docs: fix license to Apache 2.0, add hyperparameters + limitations, update citations (#3) 689d1ea

Upload model trained with Unsloth b7ab8ee verified

Update model card: fix conditions, base model, benchmarks, languages (#1) e4f13e7

init: create README.md f48842c verified

initial commit b51e5c6 verified

docs: delineate Phase 2 (Stack v1) vs Phase 3 (Stack v2-dedup) adapters

5a8663a
verified

docs: add arxiv: tags for paper bibliography anchors (#11)

aa01d9a

docs(readme): align with canonical source-of-truth (cond-5 adapters, source-file control, refined extractor) (#10)

06802f3

docs(readme): cond-5 refined-extractor banner + Phase 3 staleness fixes (#9)

625893e

docs: add condition-1-en-32k to Model Structure table (#7)

6ac3acd

docs: fix license to Apache 2.0, add hyperparameters + limitations, update citations (#3)

689d1ea

Upload model trained with Unsloth

b7ab8ee
verified

Update model card: fix conditions, base model, benchmarks, languages (#1)

e4f13e7

init: create README.md

f48842c
verified

initial commit

b51e5c6
verified