Expose metadata link to next version of the model (#182)

- Expose metadata link to next version of the model (05ca7f87447657b73816aed907a2579c74e5b2cf)


Co-authored-by: Daniel van Strien <davanstrien@users.noreply.huggingface.co>

README.md

@@ -8,9 +8,8 @@ tags:
 - pytorch
 - llama
 - llama-3
-license: other
-license_name: llama3
-license_link: LICENSE
+license: llama3
+new_version: meta-llama/Llama-3.1-8B-Instruct
 extra_gated_prompt: >-
   ### META LLAMA 3 COMMUNITY LICENSE AGREEMENT
 
@@ -185,6 +184,29 @@ extra_gated_fields:
   By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Meta Privacy Policy: checkbox
 extra_gated_description: The information you provide will be collected, stored, processed and shared in accordance with the [Meta Privacy Policy](https://www.facebook.com/privacy/policy/).
 extra_gated_button_content: Submit
+widget:
+  - example_title: Hello
+    messages:
+    - role: user
+      content: Hey my name is Julien! How are you?
+  - example_title: Winter holidays
+    messages:
+    - role: system
+      content: You are a helpful and honest assistant. Please, respond concisely and truthfully.
+    - role: user
+      content: Can you recommend a good destination for Winter holidays?
+  - example_title: Programming assistant
+    messages:
+    - role: system
+      content: You are a helpful and honest code and programming assistant. Please, respond concisely and truthfully.
+    - role: user
+      content: Write a function that computes the nth fibonacci number.
+inference:
+  parameters:
+    max_new_tokens: 300
+    stop:
+    - <|end_of_text|>
+    - <|eot_id|>
 ---
 
 ## Model Details
@@ -287,7 +309,7 @@ pipeline = transformers.pipeline(
     "text-generation",
     model=model_id,
     model_kwargs={"torch_dtype": torch.bfloat16},
-    device="auto",
+    device_map="auto",
 )
 
 messages = [
@@ -295,26 +317,20 @@ messages = [
     {"role": "user", "content": "Who are you?"},
 ]
 
-prompt = pipeline.tokenizer.apply_chat_template(
-		messages, 
-		tokenize=False, 
-		add_generation_prompt=True
-)
-
 terminators = [
     pipeline.tokenizer.eos_token_id,
     pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
 ]
 
 outputs = pipeline(
-    prompt,
+    messages,
     max_new_tokens=256,
     eos_token_id=terminators,
     do_sample=True,
     temperature=0.6,
     top_p=0.9,
 )
-print(outputs[0]["generated_text"][len(prompt):])
+print(outputs[0]["generated_text"][-1])
 ```
 
 #### Transformers AutoModelForCausalLM
@@ -432,7 +448,7 @@ For Hugging Face support, we recommend using transformers or TGI, but a similar
 
 **Overview** Llama 3 was pretrained on over 15 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets, as well as over 10M human-annotated examples. Neither the pretraining nor the fine-tuning datasets include Meta user data.
 
-**Data Freshness** The pretraining data has a cutoff of March 2023 for the 7B and December 2023 for the 70B models respectively. 
+**Data Freshness** The pretraining data has a cutoff of March 2023 for the 8B and December 2023 for the 70B models respectively. 
 
 
 ## Benchmarks 

config.json

@@ -5,7 +5,7 @@
   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 128000,
-  "eos_token_id": 128001,
+  "eos_token_id": 128009,
   "hidden_act": "silu",
   "hidden_size": 4096,
   "initializer_range": 0.02,

generation_config.json

@@ -1,6 +1,9 @@
 {
-  "_from_model_config": true,
   "bos_token_id": 128000,
   "eos_token_id": [128001, 128009],
+  "do_sample": true,
+  "temperature": 0.6,
+  "max_length": 4096,
+  "top_p": 0.9,
   "transformers_version": "4.40.0.dev0"
 }

tokenizer.json

@@ -2329,10 +2329,69 @@
     ]
   },
   "post_processor": {
-    "type": "ByteLevel",
-    "add_prefix_space": true,
-    "trim_offsets": false,
-    "use_regex": true
+    "type": "Sequence",
+    "processors": [
+      {
+        "type": "ByteLevel",
+        "add_prefix_space": true,
+        "trim_offsets": false,
+        "use_regex": true
+      },
+      {
+        "type": "TemplateProcessing",
+        "single": [
+          {
+            "SpecialToken": {
+              "id": "<|begin_of_text|>",
+              "type_id": 0
+            }
+          },
+          {
+            "Sequence": {
+              "id": "A",
+              "type_id": 0
+            }
+          }
+        ],
+        "pair": [
+          {
+            "SpecialToken": {
+              "id": "<|begin_of_text|>",
+              "type_id": 0
+            }
+          },
+          {
+            "Sequence": {
+              "id": "A",
+              "type_id": 0
+            }
+          },
+          {
+            "SpecialToken": {
+              "id": "<|begin_of_text|>",
+              "type_id": 1
+            }
+          },
+          {
+            "Sequence": {
+              "id": "B",
+              "type_id": 1
+            }
+          }
+        ],
+        "special_tokens": {
+          "<|begin_of_text|>": {
+            "id": "<|begin_of_text|>",
+            "ids": [
+              128000
+            ],
+            "tokens": [
+              "<|begin_of_text|>"
+            ]
+          }
+        }
+      }
+    ]
   },
   "decoder": {
     "type": "ByteLevel",

tokenizer_config.json

@@ -2052,7 +2052,7 @@
   "bos_token": "<|begin_of_text|>",
   "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
   "clean_up_tokenization_spaces": true,
-  "eos_token": "<|end_of_text|>",
+  "eos_token": "<|eot_id|>",
   "model_input_names": [
     "input_ids",
     "attention_mask"