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haoranxu
/
ALMA-13B-R

Text Generation
Transformers
Safetensors
llama
text-generation-inference
Model card Files Files and versions
xet
Community
13

Instructions to use haoranxu/ALMA-13B-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use haoranxu/ALMA-13B-R with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="haoranxu/ALMA-13B-R")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("haoranxu/ALMA-13B-R")
    model = AutoModelForCausalLM.from_pretrained("haoranxu/ALMA-13B-R")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use haoranxu/ALMA-13B-R with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "haoranxu/ALMA-13B-R"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "haoranxu/ALMA-13B-R",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/haoranxu/ALMA-13B-R
  • SGLang

    How to use haoranxu/ALMA-13B-R 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 "haoranxu/ALMA-13B-R" \
        --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": "haoranxu/ALMA-13B-R",
    		"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 "haoranxu/ALMA-13B-R" \
            --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": "haoranxu/ALMA-13B-R",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use haoranxu/ALMA-13B-R with Docker Model Runner:

    docker model run hf.co/haoranxu/ALMA-13B-R
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Hallucination

#12 opened almost 2 years ago by
bajindy

Beginner Questions about Formatting Dataset and hardware

#11 opened about 2 years ago by
LogicBombaklot

Adding Evaluation Results

#10 opened about 2 years ago by
leaderboard-pr-bot

When using beam search, the model's output may end prematurely.

1
#9 opened over 2 years ago by
syGOAT

New language possible?

3
#8 opened over 2 years ago by
norp90

English to Canadian French

3
#7 opened over 2 years ago by
KotaNaveen

When there is a more flexible prompt, the model tends not to output

1
#5 opened over 2 years ago by
syGOAT

Is there any ablation for unsupported languages?

1
#4 opened over 2 years ago by
AntoineBlanot

Is there any comparison with Google's MADLAD-400?

4
#3 opened over 2 years ago by
AntoineBlanot

The GPT-4 comparison is a bit too early (yet?)

4
#1 opened over 2 years ago by
cmp-nct
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