Upload folder using huggingface_hub (#3)

- b026b4c7f0f68272c80bbe470a9f423cba549bff42f9485d16da5537b458c839 (d2aabfe612801ae1d65dadf293346163a87f3ab2)
- 4ff46ad9f4f783742f80c6a2b260a11d7b9b1db5f8ec8e68a4ec7fb1b38134e6 (5d2af0f7179654bfd31a7c45500098d0ed88339b)

README.md

@@ -1,6 +1,6 @@
 ---
 thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
-base_model: PrunaAI/shenzhi-wang-Llama3-8B-Chinese-Chat-bnb-4bit-smashed
+base_model: ORIGINAL_REPO_NAME
 metrics:
 - memory_disk
 - memory_inference
@@ -31,16 +31,16 @@ tags:
 - Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
 - Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
 - Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/)
-- Join Pruna AI community on Discord [here](https://discord.gg/rskEr4BZJx) to share feedback/suggestions or get help.
+- Join Pruna AI community on Discord [here](https://discord.gg/CP4VSgck) to share feedback/suggestions or get help.
 
 ## Results
 
 ![image info](./plots.png)
 
 **Frequently Asked Questions**
-- ***How does the compression work?*** The model is compressed with [.
+- ***How does the compression work?*** The model is compressed with llm-int8.
 - ***How does the model quality change?*** The quality of the model output might vary compared to the base model.
-- ***How is the model efficiency evaluated?*** These results were obtained on HARDWARE_NAME with configuration described in `model/smash_config.json` and are obtained after a hardware warmup. The smashed model is directly compared to the original base model. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...). We recommend to directly run them in the use-case conditions to know if the smashed model can benefit you.
+- ***How is the model efficiency evaluated?*** These results were obtained with configuration described in `model/smash_config.json` and are obtained after a hardware warmup. The smashed model is directly compared to the original base model. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...). We recommend to directly run them in the use-case conditions to know if the smashed model can benefit you.
 - ***What is the model format?*** We use safetensors.
 - ***What calibration data has been used?*** If needed by the compression method, we used WikiText as the calibration data.
 - ***What is the naming convention for Pruna Huggingface models?*** We take the original model name and append "turbo", "tiny", or "green" if the smashed model has a measured inference speed, inference memory, or inference energy consumption which is less than 90% of the original base model.
@@ -52,18 +52,18 @@ tags:
 
 You can run the smashed model with these steps:
 
-0. Check requirements from the original repo PrunaAI/shenzhi-wang-Llama3-8B-Chinese-Chat-bnb-4bit-smashed installed. In particular, check python, cuda, and transformers versions.
+0. Check requirements from the original repo ORIGINAL_REPO_NAME installed. In particular, check python, cuda, and transformers versions.
 1. Make sure that you have installed quantization related packages.
     ```bash
-    REQUIREMENTS_INSTRUCTIONS
+    pip install transformers accelerate bitsandbytes>0.37.0
     ```
 2. Load & run the model.
     ```python 
    from transformers import AutoModelForCausalLM, AutoTokenizer
-   IMPORTS
+   
 
-   MODEL_LOAD
-   tokenizer = AutoTokenizer.from_pretrained("PrunaAI/shenzhi-wang-Llama3-8B-Chinese-Chat-bnb-4bit-smashed")
+   model = AutoModelForCausalLM.from_pretrained("PrunaAI/shenzhi-wang-Llama3-8B-Chinese-Chat-bnb-4bit-smashed", trust_remote_code=True, device_map='auto')
+   tokenizer = AutoTokenizer.from_pretrained("ORIGINAL_REPO_NAME")
     
    input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
     
@@ -77,7 +77,7 @@ The configuration info are in `smash_config.json`.
 
 ## Credits & License
 
-The license of the smashed model follows the license of the original model. Please check the license of the original model PrunaAI/shenzhi-wang-Llama3-8B-Chinese-Chat-bnb-4bit-smashed 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.
+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.
 
 ## Want to compress other models?
 

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/tmp/tmp8yw4nvpq",
+  "_name_or_path": "/tmp/models/tmpaakrlgubnbt2n_30",
   "architectures": [
     "LlamaForCausalLM"
   ],
@@ -7,11 +7,13 @@
   "attention_dropout": 0.0,
   "bos_token_id": 128000,
   "eos_token_id": 128009,
+  "head_dim": 128,
   "hidden_act": "silu",
   "hidden_size": 4096,
   "initializer_range": 0.02,
   "intermediate_size": 14336,
   "max_position_embeddings": 8192,
+  "mlp_bias": false,
   "model_type": "llama",
   "num_attention_heads": 32,
   "num_hidden_layers": 32,
@@ -38,8 +40,8 @@
   "rope_scaling": null,
   "rope_theta": 500000.0,
   "tie_word_embeddings": false,
-  "torch_dtype": "float16",
-  "transformers_version": "4.40.0",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.48.2",
   "use_cache": true,
   "vocab_size": 128256
 }

generation_config.json

@@ -3,5 +3,5 @@
   "bos_token_id": 128000,
   "eos_token_id": 128009,
   "pad_token_id": 128009,
-  "transformers_version": "4.40.0"
+  "transformers_version": "4.48.2"
 }

model-00001-of-00002.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8aacf45f8693ae9c3e922a0b96c5908ec2dbc5a8abfd4b68a181474f11af3fa5
-size 4977222696
+oid sha256:7bd3af4b8d013b42ff98a04c9752dd9e49ec0e08a85b4f9c6864249af8a550ea
+size 4977222984

model-00002-of-00002.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fa58069fe1c308d1e2b630d489dc7475031826c148f0b4eb3fdf53ee08f7e421
+oid sha256:288837fe79d36dadb316b2b3a2281ae44a7bbb1a425bc5d2e14766cfbcb620e2
 size 1050673280

model.safetensors.index.json

@@ -1,6 +1,6 @@
 {
   "metadata": {
-    "total_size": 6027779904
+    "total_size": 6027780128
   },
   "weight_map": {
     "lm_head.weight": "model-00002-of-00002.safetensors",

smash_config.json

@@ -1,31 +1,23 @@
 {
-    "api_key": null,
-    "verify_url": "http://johnrachwan.pythonanywhere.com",
-    "smash_config": {
-        "pruners": "None",
-        "pruning_ratio": 0.0,
-        "factorizers": "None",
-        "quantizers": "['llm-int8']",
-        "weight_quantization_bits": 4,
-        "output_deviation": 0.005,
-        "compilers": "None",
-        "static_batch": true,
-        "static_shape": true,
-        "controlnet": "None",
-        "unet_dim": 4,
-        "device": "cuda",
-        "cache_dir": "/ceph/hdd/staff/charpent/.cache/models1nmgr2p9",
-        "batch_size": 1,
-        "model_name": "shenzhi-wang/Llama3-8B-Chinese-Chat",
-        "task": "text_text_generation",
-        "max_batch_size": 1,
-        "qtype_weight": "torch.qint8",
-        "qtype_activation": "torch.quint8",
-        "qobserver": "<class 'torch.ao.quantization.observer.MinMaxObserver'>",
-        "qscheme": "torch.per_tensor_symmetric",
-        "qconfig": "x86",
-        "group_size": 128,
-        "damp_percent": 0.1,
-        "save_load_fn": "bitsandbytes"
-    }
+    "batchers": null,
+    "cachers": null,
+    "compilers": null,
+    "distillers": null,
+    "pruners": null,
+    "quantizers": "llm-int8",
+    "recoverers": null,
+    "quant_llm-int8_compute_dtype": "bfloat16",
+    "quant_llm-int8_double_quant": false,
+    "quant_llm-int8_enable_fp32_cpu_offload": false,
+    "quant_llm-int8_has_fp16_weight": false,
+    "quant_llm-int8_quant_type": "fp4",
+    "quant_llm-int8_threshold": 6.0,
+    "quant_llm-int8_weight_bits": 4,
+    "max_batch_size": 1,
+    "device": "cuda",
+    "cache_dir": "/tmp/models/tmpaakrlgub",
+    "task": "",
+    "save_load_fn": "llm-int8",
+    "save_load_fn_args": {},
+    "api_key": null
 }