Instructions to use togethercomputer/RedPajama-INCITE-7B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use togethercomputer/RedPajama-INCITE-7B-Chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="togethercomputer/RedPajama-INCITE-7B-Chat")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-7B-Chat") model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-7B-Chat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use togethercomputer/RedPajama-INCITE-7B-Chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "togethercomputer/RedPajama-INCITE-7B-Chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "togethercomputer/RedPajama-INCITE-7B-Chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/togethercomputer/RedPajama-INCITE-7B-Chat
- SGLang
How to use togethercomputer/RedPajama-INCITE-7B-Chat 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 "togethercomputer/RedPajama-INCITE-7B-Chat" \ --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": "togethercomputer/RedPajama-INCITE-7B-Chat", "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 "togethercomputer/RedPajama-INCITE-7B-Chat" \ --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": "togethercomputer/RedPajama-INCITE-7B-Chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use togethercomputer/RedPajama-INCITE-7B-Chat with Docker Model Runner:
docker model run hf.co/togethercomputer/RedPajama-INCITE-7B-Chat
update readme
Browse files
README.md
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@@ -104,14 +104,28 @@ Alan Mathison Turing (23 June 1912 – 7 June 1954) was an English computer scie
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## CPU Inference
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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# init
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1")
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1", torch_dtype=torch.bfloat16)
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# infer
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print(output_str)
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"""
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Alan Turing was a British mathematician and computer scientist. He was one of the key figures in the development of computer science and artificial intelligence. He is widely regarded as the father of computer science and artificial intelligence.
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## CPU Inference
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```python
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```python
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import torch
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import transformers
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from transformers import AutoTokenizer, AutoModelForCausalLM
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MIN_TRANSFORMERS_VERSION = '4.25.1'
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# check transformers version
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assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'
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# init
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1")
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1", torch_dtype=torch.bfloat16)
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# infer
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prompt = "<human>: Who is Alan Turing?\n<bot>:"
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inputs = tokenizer(prompt, return_tensors='pt').to(model.device)
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input_length = inputs.input_ids.shape[1]
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outputs = model.generate(
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**inputs, max_new_tokens=128, do_sample=True, temperature=0.7, top_p=0.7, top_k=50, return_dict_in_generate=True
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)
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token = outputs.sequences[0, input_length:]
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output_str = tokenizer.decode(token)
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print(output_str)
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"""
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Alan Turing was a British mathematician and computer scientist. He was one of the key figures in the development of computer science and artificial intelligence. He is widely regarded as the father of computer science and artificial intelligence.
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