Instructions to use clibrain/lince-zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use clibrain/lince-zero with Transformers:

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

pipe = pipeline("text-generation", model="clibrain/lince-zero", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("clibrain/lince-zero", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("clibrain/lince-zero", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use clibrain/lince-zero with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/clibrain/lince-zero

SGLang

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

Docker Model Runner
How to use clibrain/lince-zero with Docker Model Runner:
```
docker model run hf.co/clibrain/lince-zero
```

mrm8488 commited on Jul 4, 2023

Commit

f5f761a

1 Parent(s): 7464f67

Update README.md

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@@ -13,7 +13,7 @@ datasets:
 library_name: transformers
 ---
-LINCE (Llm for Instructions from Natural Corpus en Español) is a state-of-the-art Spanish instruction language model. Developed by **[Clibrain](https://www.clibrain.com/)**, it is a causal decoder-only model with 7B parameters. LINCE-ZERO is based on **[Falcon-7B](https://huggingface.co/tiiuae/falcon-7b/blob/main/README.md)** and has been fine-tuned using an augmented combination of the **[Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca)** and **[Dolly](https://huggingface.co/datasets/databricks/databricks-dolly-15k)** datasets, both translated into Spanish.
 The model is released under the Apache 2.0 license.
@@ -23,8 +23,6 @@ The model is released under the Apache 2.0 license.
 # Model Card for LINCE-ZERO
-**LINCE-ZERO** is a model fine-tuned on a massive and original corpus of Spanish instructions.
 # Table of Contents
 - [Model Details](#model-details)

 library_name: transformers
 ---
+**LINCE ZERO** (Llm for Instructions from Natural Corpus en Español) is a state-of-the-art Spanish instruction language model. Developed by **[Clibrain](https://www.clibrain.com/)**, it is a causal decoder-only model with 7B parameters. LINCE-ZERO is based on **[Falcon-7B](https://huggingface.co/tiiuae/falcon-7b/blob/main/README.md)** and has been fine-tuned using an augmented combination of the **[Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca)** and **[Dolly](https://huggingface.co/datasets/databricks/databricks-dolly-15k)** datasets, both translated into Spanish.
 The model is released under the Apache 2.0 license.
 # Model Card for LINCE-ZERO
 # Table of Contents
 - [Model Details](#model-details)