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#2
by
sharpenb
- opened
- README.md +5 -5
- config.json +1 -1
- model.safetensors +1 -1
- smash_config.json +1 -1
README.md
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---
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thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
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base_model:
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metrics:
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- memory_disk
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- memory_inference
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You can run the smashed model with these steps:
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0. Check requirements from the original repo
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1. Make sure that you have installed quantization related packages.
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```bash
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pip install transformers accelerate bitsandbytes>0.37.0
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model = AutoModelForCausalLM.from_pretrained("PrunaAI/neeleshg23-jamba-1.9b-7-bnb-8bit-smashed", trust_remote_code=True, device_map='auto')
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tokenizer = AutoTokenizer.from_pretrained("
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input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
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## Credits & License
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The license of the smashed model follows the license of the original model. Please check the license of the original model
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## Want to compress other models?
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- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
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-
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---
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thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
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base_model: neeleshg23/jamba-1.9b-7
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metrics:
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- memory_disk
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- memory_inference
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You can run the smashed model with these steps:
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0. Check requirements from the original repo neeleshg23/jamba-1.9b-7 installed. In particular, check python, cuda, and transformers versions.
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1. Make sure that you have installed quantization related packages.
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```bash
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pip install transformers accelerate bitsandbytes>0.37.0
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model = AutoModelForCausalLM.from_pretrained("PrunaAI/neeleshg23-jamba-1.9b-7-bnb-8bit-smashed", trust_remote_code=True, device_map='auto')
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tokenizer = AutoTokenizer.from_pretrained("neeleshg23/jamba-1.9b-7")
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input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
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## Credits & License
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The license of the smashed model follows the license of the original model. Please check the license of the original model neeleshg23/jamba-1.9b-7 before using this model which provided the base model. The license of the `pruna-engine` is [here](https://pypi.org/project/pruna-engine/) on Pypi.
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## Want to compress other models?
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- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
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- Do it by yourself [here](https://docs.pruna.ai/en/latest/setup/pip.html).
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config.json
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{
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"_name_or_path": "/covalent/.cache/models/
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"architectures": [
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"JambaForCausalLM"
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],
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{
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"_name_or_path": "/covalent/.cache/models/tmp_52zyzai_lzq9dm2",
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"architectures": [
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"JambaForCausalLM"
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],
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 2425351143
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version https://git-lfs.github.com/spec/v1
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oid sha256:7be7cf1530fd026f370bd5a3955e8760139d14c19157325ae38f67e9a4520095
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size 2425351143
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smash_config.json
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"quant_llm-int8_weight_bits": 8,
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"max_batch_size": 1,
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"device": "cuda",
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"cache_dir": "/covalent/.cache/models/
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"task": "",
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"save_load_fn": "bitsandbytes",
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"save_load_fn_args": {}
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"quant_llm-int8_weight_bits": 8,
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"max_batch_size": 1,
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"device": "cuda",
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"cache_dir": "/covalent/.cache/models/tmp_52zyzai",
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"task": "",
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"save_load_fn": "bitsandbytes",
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"save_load_fn_args": {}
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