Instructions to use FPHam/Rachel_Assistant_Editor_13b_GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FPHam/Rachel_Assistant_Editor_13b_GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FPHam/Rachel_Assistant_Editor_13b_GPTQ")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FPHam/Rachel_Assistant_Editor_13b_GPTQ") model = AutoModelForCausalLM.from_pretrained("FPHam/Rachel_Assistant_Editor_13b_GPTQ") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use FPHam/Rachel_Assistant_Editor_13b_GPTQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FPHam/Rachel_Assistant_Editor_13b_GPTQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FPHam/Rachel_Assistant_Editor_13b_GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/FPHam/Rachel_Assistant_Editor_13b_GPTQ
- SGLang
How to use FPHam/Rachel_Assistant_Editor_13b_GPTQ 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 "FPHam/Rachel_Assistant_Editor_13b_GPTQ" \ --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": "FPHam/Rachel_Assistant_Editor_13b_GPTQ", "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 "FPHam/Rachel_Assistant_Editor_13b_GPTQ" \ --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": "FPHam/Rachel_Assistant_Editor_13b_GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use FPHam/Rachel_Assistant_Editor_13b_GPTQ with Docker Model Runner:
docker model run hf.co/FPHam/Rachel_Assistant_Editor_13b_GPTQ
Update README.md
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README.md
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@@ -64,6 +64,17 @@ cash should hook up with someone from the neighborhood.
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Rewrite the following text reversing the genders
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It is a truth universally acknowledged, that a single woman in
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```
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Rewrite the following text the way Zapp Brannigan from Futurama talks
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```
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Y'know, it's a fact, sonny, that any fella with a bit o' money to spare
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has gotta find himself a missus.
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They all know the score - ain't no secret that when a new face rolls into town,
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there's gonna be some lucky lady claimin' him for her own.
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Ain't nothin' like it in their heads, mind you, but they don't need no fancy
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talkers to figure out who gets dibs on 'em.
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```
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Rewrite the following text reversing the genders
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```
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It is a truth universally acknowledged, that a single woman in
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