1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
|
import ClassPropertyRef from '@site/src/components/ClassPropertyRef.tsx';
# HuggingFaceInferenceAPI
Hugging Face Inference API is a great option for newly released language models. Sign up for an account and add billing [here](https://huggingface.co/settings/billing), access the Inference Endpoints [here](https://ui.endpoints.huggingface.co), click on “New endpoint”, and fill out the form (e.g. select a model like [WizardCoder-Python-34B-V1.0](https://huggingface.co/WizardLM/WizardCoder-Python-34B-V1.0)), and then deploy your model by clicking “Create Endpoint”. Change `~/.continue/config.py` to look like this:
```python title="~/.continue/config.py"
from continuedev.src.continuedev.core.models import Models
from continuedev.src.continuedev.libs.llm.hf_inference_api import HuggingFaceInferenceAPI
config = ContinueConfig(
...
models=Models(
default=HuggingFaceInferenceAPI(
endpoint_url: "<INFERENCE_API_ENDPOINT_URL>",
hf_token: "<HUGGING_FACE_TOKEN>",
)
)
```
[View the source](https://github.com/continuedev/continue/tree/main/continuedev/src/continuedev/libs/llm/hf_inference_api.py)
## Properties
<ClassPropertyRef name='hf_token' details='{"title": "Hf Token", "description": "Your Hugging Face API token", "type": "string"}' required={true} default=""/>
<ClassPropertyRef name='endpoint_url' details='{"title": "Endpoint Url", "description": "Your Hugging Face Inference API endpoint URL", "type": "string"}' required={false} default=""/>
### Inherited Properties
<ClassPropertyRef name='title' details='{"title": "Title", "description": "A title that will identify this model in the model selection dropdown", "type": "string"}' required={false} default=""/>
<ClassPropertyRef name='system_message' details='{"title": "System Message", "description": "A system message that will always be followed by the LLM", "type": "string"}' required={false} default=""/>
<ClassPropertyRef name='context_length' details='{"title": "Context Length", "description": "The maximum context length of the LLM in tokens, as counted by count_tokens.", "default": 2048, "type": "integer"}' required={false} default="2048"/>
<ClassPropertyRef name='unique_id' details='{"title": "Unique Id", "description": "The unique ID of the user.", "type": "string"}' required={false} default=""/>
<ClassPropertyRef name='model' details='{"title": "Model", "description": "The name of the model to use (optional for the HuggingFaceInferenceAPI class)", "default": "Hugging Face Inference API", "type": "string"}' required={false} default="Hugging Face Inference API"/>
<ClassPropertyRef name='max_tokens' details='{"title": "Max Tokens", "description": "The maximum number of tokens to generate.", "default": 1024, "type": "integer"}' required={false} default="1024"/>
<ClassPropertyRef name='stop_tokens' details='{"title": "Stop Tokens", "description": "Tokens that will stop the completion.", "type": "array", "items": {"type": "string"}}' required={false} default=""/>
<ClassPropertyRef name='timeout' details='{"title": "Timeout", "description": "Set the timeout for each request to the LLM. If you are running a local LLM that takes a while to respond, you might want to set this to avoid timeouts.", "default": 300, "type": "integer"}' required={false} default="300"/>
<ClassPropertyRef name='verify_ssl' details='{"title": "Verify Ssl", "description": "Whether to verify SSL certificates for requests.", "type": "boolean"}' required={false} default=""/>
<ClassPropertyRef name='ca_bundle_path' details='{"title": "Ca Bundle Path", "description": "Path to a custom CA bundle to use when making the HTTP request", "type": "string"}' required={false} default=""/>
<ClassPropertyRef name='proxy' details='{"title": "Proxy", "description": "Proxy URL to use when making the HTTP request", "type": "string"}' required={false} default=""/>
<ClassPropertyRef name='prompt_templates' details='{"title": "Prompt Templates", "description": "A dictionary of prompt templates that can be used to customize the behavior of the LLM in certain situations. For example, set the \"edit\" key in order to change the prompt that is used for the /edit slash command. Each value in the dictionary is a string templated in mustache syntax, and filled in at runtime with the variables specific to the situation. See the documentation for more information.", "default": {"edit": "Consider the following code:\n```\n{{{code_to_edit}}}\n```\nEdit the code to perfectly satisfy the following user request:\n{{{user_input}}}\nOutput nothing except for the code. No code block, no English explanation, no start/end tags."}, "type": "object"}' required={false} default="{'edit': 'Consider the following code:\n```\n{{{code_to_edit}}}\n```\nEdit the code to perfectly satisfy the following user request:\n{{{user_input}}}\nOutput nothing except for the code. No code block, no English explanation, no start/end tags.'}"/>
<ClassPropertyRef name='api_key' details='{"title": "Api Key", "description": "The API key for the LLM provider.", "type": "string"}' required={false} default=""/>
|
