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#2
by sharpenb - opened
Files changed (4) hide show
  1. README.md +5 -5
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. smash_config.json +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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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: ORIGINAL_REPO_NAME
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  metrics:
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  - memory_disk
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  - memory_inference
@@ -52,7 +52,7 @@ tags:
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  You can run the smashed model with these steps:
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- 0. Check requirements from the original repo ORIGINAL_REPO_NAME 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
@@ -63,7 +63,7 @@ You can run the smashed model with these steps:
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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("ORIGINAL_REPO_NAME")
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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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@@ -77,9 +77,9 @@ The configuration info are in `smash_config.json`.
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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 ORIGINAL_REPO_NAME 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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- - Request access to easily compress your own AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
 
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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).
config.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "_name_or_path": "/covalent/.cache/models/tmp0n_hx_3e9y8ksise",
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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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  ],
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:0391bbf2ec4f9b3f9c88e358b8d0bfc6f4e066cdf4aef7a96060582f8b5ab5e5
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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
smash_config.json CHANGED
@@ -28,7 +28,7 @@
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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/tmp0n_hx_3e",
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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": {}