Related to #10800
- Errors in the Docstring of GradientLLM / Gradient.ai LLM
- Renamed the `model_id` to `model` and adapting this in all tests.
Reason to so is to be in Sync with `GradientEmbeddings` and other LLM's.
- inmproving tests so they check the headers in the sent request.
- making the aiosession a private attribute in the docs, as in the
future `pip install gradientai` will be replacing aiosession.
- adding a example how to fine-tune on the Prompt Template as suggested
in #10800
"if not os.environ.get(\"GRADIENT_ACCESS_TOKEN\",None):\n",
" # Access token under https://auth.gradient.ai/select-workspace\n",
@ -61,7 +59,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Optional: Validate your Environment variables ```GRADIENT_ACCESS_TOKEN``` and ```GRADIENT_WORKSPACE_ID``` to get currently deployed models."
"Optional: Validate your Enviroment variables ```GRADIENT_ACCESS_TOKEN``` and ```GRADIENT_WORKSPACE_ID``` to get currently deployed models. Using the `gradientai` Python package."
"You can specify different parameters such as the model name, max tokens generated, temperature, etc."
"You can specify different parameters such as the model, max_tokens generated, temperature, etc.\n",
"\n",
"As we later want to fine-tune out model, we select the model_adapter with the id `674119b5-f19e-4856-add2-767ae7f7d7ef_model_adapter`, but you can use any base or fine-tunable model."
>[Gradient](https://gradient.ai/) allows to fine tune and get completions on LLMs with a simple web API.
## Installation and Setup
- Install the Python SDK :
```bash
pip install gradientai
```
Get a [Gradient access token and workspace](https://gradient.ai/) and set it as an environment variable (`Gradient_ACCESS_TOKEN`) and (`GRADIENT_WORKSPACE_ID`)
## LLM
There exists an Gradient LLM wrapper, which you can access with
See a [usage example](/docs/integrations/llms/gradient).
```python
from langchain.llms import GradientLLM
```
## Text Embedding Model
There exists an Gradient Embedding model, which you can access with
```python
from langchain.embeddings import GradientEmbeddings
```
For a more detailed walkthrough of this, see [this notebook](/docs/integrations/text_embedding/gradient.html)
Michael Feil
12 months ago
committed by
GitHub