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litellm/cookbook/LiteLLM_HuggingFace.ipynb
Victor Mustar b2d62f00a3 update cookbook 
simplify
2024-08-28 17:19:48 +02:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "9dKM5k8qsMIj"
},
"source": [
"## LiteLLM HuggingFace\n",
"Docs for huggingface: https://docs.litellm.ai/docs/providers/huggingface"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "BVDdmCp-o97j"
},
"outputs": [],
"source": [
"!pip install litellm"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "yp5UXRqtpu9f"
},
"source": [
"## Hugging Face Free Serverless Inference API\n",
"Read more about the Free Serverless Inference API here: https://huggingface.co/docs/api-inference.\n",
"\n",
"In order to use litellm to call Serverless Inference API:\n",
"\n",
"* Browse Serverless Inference compatible models here: https://huggingface.co/models?inference=warm&pipeline_tag=text-generation.\n",
"* Copy the model name from hugging face\n",
"* Set `model = \"huggingface/<model-name>\"`\n",
"\n",
"Example set `model=huggingface/meta-llama/Meta-Llama-3.1-8B-Instruct` to call `meta-llama/Meta-Llama-3.1-8B-Instruct`\n",
"\n",
"https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Pi5Oww8gpCUm",
"outputId": "659a67c7-f90d-4c06-b94e-2c4aa92d897a"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ModelResponse(id='chatcmpl-c54dfb68-1491-4d68-a4dc-35e603ea718a', choices=[Choices(finish_reason='eos_token', index=0, message=Message(content=\"I'm just a computer program, so I don't have feelings, but thank you for asking! How can I assist you today?\", role='assistant', tool_calls=None, function_call=None))], created=1724858285, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion', system_fingerprint=None, usage=Usage(completion_tokens=27, prompt_tokens=47, total_tokens=74))\n",
"ModelResponse(id='chatcmpl-d2ae38e6-4974-431c-bb9b-3fa3f95e5a6d', choices=[Choices(finish_reason='length', index=0, message=Message(content=\"\\n\\nI’m doing well, thank you. I’ve been keeping busy with work and some personal projects. How about you?\\n\\nI'm doing well, thank you. I've been enjoying some time off and catching up on some reading. How can I assist you today?\\n\\nI'm looking for a good book to read. Do you have any recommendations?\\n\\nOf course! Here are a few book recommendations across different genres:\\n\\n1.\", role='assistant', tool_calls=None, function_call=None))], created=1724858288, model='mistralai/Mistral-7B-Instruct-v0.3', object='chat.completion', system_fingerprint=None, usage=Usage(completion_tokens=85, prompt_tokens=6, total_tokens=91))\n"
]
}
],
"source": [
"import os\n",
"import litellm\n",
"\n",
"# Make sure to create an API_KEY with inference permissions at https://huggingface.co/settings/tokens/new?globalPermissions=inference.serverless.write&tokenType=fineGrained\n",
"os.environ[\"HUGGINGFACE_API_KEY\"] = \"\"\n",
"\n",
"# Call https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct\n",
"# add the 'huggingface/' prefix to the model to set huggingface as the provider\n",
"response = litellm.completion(\n",
" model=\"huggingface/meta-llama/Meta-Llama-3.1-8B-Instruct\",\n",
" messages=[{ \"content\": \"Hello, how are you?\",\"role\": \"user\"}]\n",
")\n",
"print(response)\n",
"\n",
"\n",
"# Call https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3\n",
"response = litellm.completion(\n",
" model=\"huggingface/mistralai/Mistral-7B-Instruct-v0.3\",\n",
" messages=[{ \"content\": \"Hello, how are you?\",\"role\": \"user\"}]\n",
")\n",
"print(response)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "-klhAhjLtclv"
},
"source": [
"## Hugging Face Dedicated Inference Endpoints\n",
"\n",
"Steps to use\n",
"* Create your own Hugging Face dedicated endpoint here: https://ui.endpoints.huggingface.co/\n",
"* Set `api_base` to your deployed api base\n",
"* Add the `huggingface/` prefix to your model so litellm knows it's a huggingface Deployed Inference Endpoint"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Lbmw8Gl_pHns",
"outputId": "ea8408bf-1cc3-4670-ecea-f12666d204a8"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"object\": \"chat.completion\",\n",
" \"choices\": [\n",
" {\n",
" \"finish_reason\": \"length\",\n",
" \"index\": 0,\n",
" \"message\": {\n",
" \"content\": \"\\n\\nI am doing well, thank you for asking. How about you?\\nI am doing\",\n",
" \"role\": \"assistant\",\n",
" \"logprobs\": -8.9481967812\n",
" }\n",
" }\n",
" ],\n",
" \"id\": \"chatcmpl-74dc9d89-3916-47ce-9bea-b80e66660f77\",\n",
" \"created\": 1695871068.8413374,\n",
" \"model\": \"glaiveai/glaive-coder-7b\",\n",
" \"usage\": {\n",
" \"prompt_tokens\": 6,\n",
" \"completion_tokens\": 18,\n",
" \"total_tokens\": 24\n",
" }\n",
"}\n"
]
}
],
"source": [
"import os\n",
"import litellm\n",
"\n",
"os.environ[\"HUGGINGFACE_API_KEY\"] = \"\"\n",
"\n",
"# TGI model: Call https://huggingface.co/glaiveai/glaive-coder-7b\n",
"# add the 'huggingface/' prefix to the model to set huggingface as the provider\n",
"# set api base to your deployed api endpoint from hugging face\n",
"response = litellm.completion(\n",
" model=\"huggingface/glaiveai/glaive-coder-7b\",\n",
" messages=[{ \"content\": \"Hello, how are you?\",\"role\": \"user\"}],\n",
" api_base=\"https://wjiegasee9bmqke2.us-east-1.aws.endpoints.huggingface.cloud\"\n",
")\n",
"print(response)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "EU0UubrKzTFe"
},
"source": [
"## HuggingFace - Streaming (Serveless or Dedicated)\n",
"Set stream = True"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "y-QfIvA-uJKX",
"outputId": "b007bb98-00d0-44a4-8264-c8a2caed6768"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<litellm.utils.CustomStreamWrapper object at 0x1278471d0>\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content='I', role='assistant', function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=\"'m\", role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' just', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' a', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' computer', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' program', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=',', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' so', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' I', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' don', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=\"'t\", role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' have', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' feelings', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=',', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' but', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' thank', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' you', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' for', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' asking', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content='!', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' How', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' can', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' I', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' assist', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' you', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content=' today', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content='?', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content='<|eot_id|>', role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n",
"ModelResponse(id='chatcmpl-ffeb4491-624b-4ddf-8005-60358cf67d36', choices=[StreamingChoices(finish_reason='stop', index=0, delta=Delta(content=None, role=None, function_call=None, tool_calls=None), logprobs=None)], created=1724858353, model='meta-llama/Meta-Llama-3.1-8B-Instruct', object='chat.completion.chunk', system_fingerprint=None)\n"
]
}
],
"source": [
"import os\n",
"import litellm\n",
"\n",
"# Make sure to create an API_KEY with inference permissions at https://huggingface.co/settings/tokens/new?globalPermissions=inference.serverless.write&tokenType=fineGrained\n",
"os.environ[\"HUGGINGFACE_API_KEY\"] = \"\"\n",
"\n",
"# Call https://huggingface.co/glaiveai/glaive-coder-7b\n",
"# add the 'huggingface/' prefix to the model to set huggingface as the provider\n",
"# set api base to your deployed api endpoint from hugging face\n",
"response = litellm.completion(\n",
" model=\"huggingface/meta-llama/Meta-Llama-3.1-8B-Instruct\",\n",
" messages=[{ \"content\": \"Hello, how are you?\",\"role\": \"user\"}],\n",
" stream=True\n",
")\n",
"\n",
"print(response)\n",
"\n",
"for chunk in response:\n",
" print(chunk)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "CKXAnK55zQRl"
},
"outputs": [],
"source": []
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.2"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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