Push model using huggingface_hub.

README.md

@@ -25,7 +25,7 @@ You can then generate text as follows:
 ```python
 from transformers import pipeline
 
-generator = pipeline("text-generation", model="nteku1//tmp/tmpeczj8d97/nteku1/firstppomodel")
+generator = pipeline("text-generation", model="nteku1//tmp/tmpwi2wt4ig/nteku1/firstppomodel")
 outputs = generator("Hello, my llama is cute")
 ```
 
@@ -35,8 +35,8 @@ If you want to use the model for training or to obtain the outputs from the valu
 from transformers import AutoTokenizer
 from trl import AutoModelForCausalLMWithValueHead
 
-tokenizer = AutoTokenizer.from_pretrained("nteku1//tmp/tmpeczj8d97/nteku1/firstppomodel")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("nteku1//tmp/tmpeczj8d97/nteku1/firstppomodel")
+tokenizer = AutoTokenizer.from_pretrained("nteku1//tmp/tmpwi2wt4ig/nteku1/firstppomodel")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("nteku1//tmp/tmpwi2wt4ig/nteku1/firstppomodel")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5da979194b4e65f142613b5ed61d003101351fe01d80d89e0c9fae8bb69a96c8
+oid sha256:d46fe139897b8f7906e860e5e1f3eeeb3174d96c7e45580ca2728406371a3a2e
 size 6652

tokenizer.json

@@ -1,21 +1,7 @@
 {
   "version": "1.0",
-  "truncation": {
-    "direction": "Right",
-    "max_length": 512,
-    "strategy": "LongestFirst",
-    "stride": 0
-  },
-  "padding": {
-    "strategy": {
-      "Fixed": 512
-    },
-    "direction": "Right",
-    "pad_to_multiple_of": null,
-    "pad_id": 50256,
-    "pad_type_id": 0,
-    "pad_token": "<|endoftext|>"
-  },
+  "truncation": null,
+  "padding": null,
   "added_tokens": [
     {
       "id": 50256,