Upload folder using huggingface_hub (#2)

- 2f35b8e62e7333ef476fde24920d952f963057f95ab0ba19c95e07b2854d069f (31b01c1887fa084fbb908c1b0b1032135ffe5d80)
- c87c84ca17b9d406d35cb6259de32538445ac42650d1f667aa0744a98eb9b449 (e2d923cdbd1d05034274fa50898495a858868a27)

README.md

@@ -34,7 +34,7 @@ tags:
 
 ## Results
 
-Detailed efficiency metrics coming soon!
+![image info](./plots.png)
 
 **Frequently Asked Questions**
 - ***How does the compression work?*** The model is compressed with llm-int8.
@@ -61,7 +61,7 @@ You can run the smashed model with these steps:
    from transformers import AutoModelForCausalLM, AutoTokenizer
 
     model = AutoModelForCausalLM.from_pretrained("PrunaAI/lmsys-vicuna-7b-v1.5-16k-bnb-4bit-smashed",
-                                                 trust_remote_code=True)
+                                                 trust_remote_code=True, device_map='auto')
     tokenizer = AutoTokenizer.from_pretrained("lmsys/vicuna-7b-v1.5-16k")
     
     input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/tmp/tmpanp7ex08",
+  "_name_or_path": "/tmp/tmp22ecq2mz",
   "architectures": [
     "LlamaForCausalLM"
   ],
@@ -22,7 +22,7 @@
   "quantization_config": {
     "bnb_4bit_compute_dtype": "bfloat16",
     "bnb_4bit_quant_type": "fp4",
-    "bnb_4bit_use_double_quant": true,
+    "bnb_4bit_use_double_quant": false,
     "llm_int8_enable_fp32_cpu_offload": false,
     "llm_int8_has_fp16_weight": false,
     "llm_int8_skip_modules": [

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e829ecb9695fd1cd0fbb5248cc05172592effa36be0c3596827da20337a07a37
-size 3866042097
+oid sha256:44ec9f610a3568be7562acd06d18144cb333f90c54c2701daa2c022e4988839b
+size 4167722008

smash_config.json

@@ -8,7 +8,7 @@
         "compilers": "None",
         "task": "text_text_generation",
         "device": "cuda",
-        "cache_dir": "/ceph/hdd/staff/charpent/.cache/modelszcbmeeea",
+        "cache_dir": "/ceph/hdd/staff/charpent/.cache/models4p09tmuw",
         "batch_size": 1,
         "model_name": "lmsys/vicuna-7b-v1.5-16k",
         "pruning_ratio": 0.0,