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README.md

@@ -8,18 +8,187 @@ language:
 - hi
 - es
 - th
+license: llama3.1
+base_model: meta-llama/Meta-Llama-3.1-8B
 pipeline_tag: text-generation
 tags:
 - facebook
 - meta
+- pytorch
 - llama
 - llama-3
-license: llama3.1
-
+extra_gated_prompt: "### LLAMA 3.1 COMMUNITY LICENSE AGREEMENT\nLlama 3.1 Version\
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+  \ to this Agreement. The courts of California shall have exclusive jurisdiction\
+  \ of any dispute arising out of this Agreement.\n### Llama 3.1 Acceptable Use Policy\n\
+  Meta is committed to promoting safe and fair use of its tools and features, including\
+  \ Llama 3.1. If you access or use Llama 3.1, you agree to this Acceptable Use Policy\
+  \ (“Policy”). The most recent copy of this policy can be found at [https://llama.meta.com/llama3_1/use-policy](https://llama.meta.com/llama3_1/use-policy)\n\
+  #### Prohibited Uses\nWe want everyone to use Llama 3.1 safely and responsibly.\
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+  \ of Llama 3.1 related to the following:\n    1. Generating, promoting, or furthering\
+  \ fraud or the creation or promotion of disinformation\n    2. Generating, promoting,\
+  \ or furthering defamatory content, including the creation of defamatory statements,\
+  \ images, or other content\n    3. Generating, promoting, or further distributing\
+  \ spam\n    4. Impersonating another individual without consent, authorization,\
+  \ or legal right\n    5. Representing that the use of Llama 3.1 or outputs are human-generated\n\
+  \    6. Generating or facilitating false online engagement, including fake reviews\
+  \ and other means of fake online engagement\n4. Fail to appropriately disclose to\
+  \ end users any known dangers of your AI system\nPlease report any violation of\
+  \ this Policy, software “bug,” or other problems that could lead to a violation\
+  \ of this Policy through one of the following means:\n    * Reporting issues with\
+  \ the model: [https://github.com/meta-llama/llama-models/issues](https://github.com/meta-llama/llama-models/issues)\n\
+  \    * Reporting risky content generated by the model:\n    developers.facebook.com/llama_output_feedback\n\
+  \    * Reporting bugs and security concerns: facebook.com/whitehat/info\n    * Reporting\
+  \ violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3: [email protected]"
+extra_gated_fields:
+  First Name: text
+  Last Name: text
+  Date of birth: date_picker
+  Country: country
+  Affiliation: text
+  Job title:
+    type: select
+    options:
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+    - AI researcher
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+    - Reporter
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+  geo: ip_location
+  ? By clicking Submit below I accept the terms of the license and acknowledge that
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+    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
 ---
 
-Exl2 quant version using exllamav2 dev branch to fix RoPE
-
 ## Model Information
 
 The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.
@@ -155,6 +324,52 @@ print(outputs[0]["generated_text"][-1])
 
 Note: You can also find detailed recipes on how to use the model locally, with `torch.compile()`, assisted generations, quantised and more at [`huggingface-llama-recipes`](https://github.com/huggingface/huggingface-llama-recipes)
 
+### Tool use with transformers
+
+LLaMA-3.1 supports multiple tool use formats. You can see a full guide to prompt formatting [here](https://llama.meta.com/docs/model-cards-and-prompt-formats/llama3_1/).
+
+Tool use is also supported through [chat templates](https://huggingface.co/docs/transformers/main/chat_templating#advanced-tool-use--function-calling) in Transformers. 
+Here is a quick example showing a single simple tool:
+
+```python
+# First, define a tool
+def get_current_temperature(location: str) -> float:
+    """
+    Get the current temperature at a location.
+    
+    Args:
+        location: The location to get the temperature for, in the format "City, Country"
+    Returns:
+        The current temperature at the specified location in the specified units, as a float.
+    """
+    return 22.  # A real function should probably actually get the temperature!
+
+# Next, create a chat and apply the chat template
+messages = [
+  {"role": "system", "content": "You are a bot that responds to weather queries."},
+  {"role": "user", "content": "Hey, what's the temperature in Paris right now?"}
+]
+
+inputs = tokenizer.apply_chat_template(messages, tools=[get_current_temperature], add_generation_prompt=True)
+```
+
+You can then generate text from this input as normal. If the model generates a tool call, you should add it to the chat like so:
+
+```python
+tool_call = {"name": "get_current_temperature", "arguments": {"location": "Paris, France"}}
+messages.append({"role": "assistant", "tool_calls": [{"type": "function", "function": tool_call}]})
+```
+
+and then call the tool and append the result, with the `tool` role, like so:
+
+```python
+messages.append({"role": "tool", "name": "get_current_temperature", "content": "22.0"})
+```
+
+After that, you can `generate()` again to let the model use the tool result in the chat. Note that this was a very brief introduction to tool calling - for more information,
+see the [LLaMA prompt format docs](https://llama.meta.com/docs/model-cards-and-prompt-formats/llama3_1/) and the Transformers [tool use documentation](https://huggingface.co/docs/transformers/main/chat_templating#advanced-tool-use--function-calling).
+
+
 ### Use with `llama`
 
 Please, follow the instructions in the [repository](https://github.com/meta-llama/llama)

config.json

@@ -37,7 +37,7 @@
     "vocab_size": 128256,
     "quantization_config": {
         "quant_method": "exl2",
-        "version": "0.1.7",
+        "version": "0.1.9",
         "bits": 8.0,
         "head_bits": 6,
         "calibration": {

output.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:117d6f439e2482061da4cf65acd8aea850b9b4f73ea34d0e94ba221d2ed3b321
-size 8420608664
+oid sha256:4c9e1de031a0ee0d34e81db83caaa0cc1f02ba0e1f6d32271dd388dad6ae4973
+size 8374843636

special_tokens_map.json

@@ -1,4 +1,16 @@
 {
-  "bos_token": "<|begin_of_text|>",
-  "eos_token": "<|eot_id|>"
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
 }

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

@@ -2050,7 +2050,7 @@
     }
   },
   "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 %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n    {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n            {%- for arg_name, arg_val in tool_call.arguments | items %}\n                {{- arg_name + '=\"' + arg_val + '\"' }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n                {%- endfor %}\n            {{- \")\" }}\n        {%- else  %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n            {{- '\"parameters\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- \"}\" }}\n        {%- endif %}\n        {%- if builtin_tools is defined %}\n            {#- This means we're in ipython mode #}\n            {{- \"<|eom_id|>\" }}\n        {%- else %}\n            {{- \"<|eot_id|>\" }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
   "clean_up_tokenization_spaces": true,
   "eos_token": "<|eot_id|>",
   "model_input_names": [