Upload folder using huggingface_hub (#2)

- 37c33a99fa16dd308bfbd948e97f9c19b5028f80f16be2b394f6f6dbf3e56bef (70ffb556e1536f81c6c235fb5e639e207f678504)
- 3b463e7e410d2f1aea38959fa06c8c2f1747f624bd85935cdc17466ee17b5c1c (c430de2dabfe31c1ea67d52f5d336d278fea9928)

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/llm-agents-tora-code-7b-v1.0-bnb-4bit-smashed",
-                                                 trust_remote_code=True)
+                                                 trust_remote_code=True, device_map='auto')
     tokenizer = AutoTokenizer.from_pretrained("llm-agents/tora-code-7b-v1.0")
     
     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/tmp3nxm24kx",
+  "_name_or_path": "/tmp/tmpya0efvmp",
   "architectures": [
     "LlamaForCausalLM"
   ],
@@ -21,7 +21,7 @@
   "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:ae99f60a13492af7d37444967528f89083537e2b811574329ca29f963dd10fed
-size 3866058418
+oid sha256:ad61780305a987be113c8a0d55dd6af97a6763ef4b27a4a6069f6a46c8645a09
+size 4167738392

smash_config.json

@@ -8,7 +8,7 @@
         "compilers": "None",
         "task": "text_text_generation",
         "device": "cuda",
-        "cache_dir": "/ceph/hdd/staff/charpent/.cache/modelshyof0ywr",
+        "cache_dir": "/ceph/hdd/staff/charpent/.cache/models_3mqw4kh",
         "batch_size": 1,
         "model_name": "llm-agents/tora-code-7b-v1.0",
         "pruning_ratio": 0.0,