openapi: 3.0.3
info:
title: remediation.proto Audio Fine-tuning API
version: version not set
servers:
- url: https://api.together.xyz/v1
security:
- bearerAuth: []
tags:
- name: Fine-tuning
paths:
/fine-tunes:
post:
tags:
- Fine-tuning
summary: Create job
description: Create a fine-tuning job with the provided model and training data.
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: "# Docs for v1 can be found by changing the above selector ^\nfrom together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.create(\n model=\"meta-llama/Meta-Llama-3.1-8B-Instruct-Reference\",\n training_file=\"file-id\"\n)\n\nprint(response)\n"
- lang: Python
label: Together AI SDK (v1)
source: "from together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.create(\n model=\"meta-llama/Meta-Llama-3.1-8B-Instruct-Reference\",\n training_file=\"file-id\"\n)\n\nprint(response)\n"
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.create({\n model: \"meta-llama/Meta-Llama-3.1-8B-Instruct-Reference\",\n training_file: \"file-id\",\n});\n\nconsole.log(response);\n"
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.create({\n model: \"meta-llama/Meta-Llama-3.1-8B-Instruct-Reference\",\n training_file: \"file-id\",\n});\n\nconsole.log(response);\n"
- lang: Shell
label: cURL
source: "curl -X POST \"https://api.together.ai/v1/fine-tunes\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"meta-llama/Meta-Llama-3.1-8B-Instruct-Reference\",\n \"training_file\": \"file-id\"\n }'\n"
requestBody:
required: true
content:
application/json:
schema:
type: object
required:
- training_file
- model
properties:
training_file:
type: string
description: File-ID of a training file uploaded to the Together API
validation_file:
type: string
description: File-ID of a validation file uploaded to the Together API
packing:
type: boolean
default: true
description: Whether to use sequence packing for training.
max_seq_length:
type: integer
description: Maximum sequence length to use for training.
model:
type: string
description: Name of the base model to run fine-tune job on
n_epochs:
type: integer
default: 1
description: Number of complete passes through the training dataset (higher values may improve results but increase cost and risk of overfitting)
n_checkpoints:
type: integer
default: 1
description: Number of intermediate model versions saved during training for evaluation
n_evals:
type: integer
default: 0
description: Number of evaluations to be run on a given validation set during training
batch_size:
oneOf:
- type: integer
- type: string
enum:
- max
default: max
description: Number of training examples processed together (larger batches use more memory but may train faster). Defaults to "max". We use training optimizations like packing, so the effective batch size may be different than the value you set.
learning_rate:
type: number
format: float
default: 1.0e-05
description: Controls how quickly the model adapts to new information (too high may cause instability, too low may slow convergence)
lr_scheduler:
type: object
default: none
$ref: '#/components/schemas/LRScheduler'
description: The learning rate scheduler to use. It specifies how the learning rate is adjusted during training.
warmup_ratio:
type: number
format: float
default: 0
description: The percent of steps at the start of training to linearly increase the learning rate.
max_grad_norm:
type: number
format: float
default: 1
description: Max gradient norm to be used for gradient clipping. Set to 0 to disable.
weight_decay:
type: number
format: float
default: 0
description: Weight decay. Regularization parameter for the optimizer.
random_seed:
type: integer
nullable: true
description: 'Random seed for reproducible training. When set, the same seed produces the same run (e.g. data shuffle, init). If omitted or null, the server applies its default seed (e.g. 42).
'
suffix:
type: string
description: Suffix that will be added to your fine-tuned model name
wandb_api_key:
type: string
description: Integration key for tracking experiments and model metrics on W&B platform
wandb_base_url:
type: string
description: The base URL of a dedicated Weights & Biases instance.
wandb_project_name:
type: string
description: The Weights & Biases project for your run. If not specified, will use `together` as the project name.
wandb_name:
type: string
description: The Weights & Biases name for your run.
wandb_entity:
type: string
description: The Weights & Biases entity for your run.
train_on_inputs:
oneOf:
- type: boolean
- type: string
enum:
- auto
type: boolean
default: auto
description: Whether to mask the user messages in conversational data or prompts in instruction data.
deprecated: true
training_method:
type: object
oneOf:
- $ref: '#/components/schemas/TrainingMethodSFT'
- $ref: '#/components/schemas/TrainingMethodDPO'
description: The training method to use. 'sft' for Supervised Fine-Tuning or 'dpo' for Direct Preference Optimization.
training_type:
type: object
default: null
nullable: true
anyOf:
- $ref: '#/components/schemas/FullTrainingType'
- $ref: '#/components/schemas/LoRATrainingType'
description: The training type to use. If not provided, the job will default to LoRA training type.
multimodal_params:
$ref: '#/components/schemas/MultimodalParams'
from_checkpoint:
type: string
description: The checkpoint identifier to continue training from a previous fine-tuning job. Format is `{$JOB_ID}` or `{$OUTPUT_MODEL_NAME}` or `{$JOB_ID}:{$STEP}` or `{$OUTPUT_MODEL_NAME}:{$STEP}`. The step value is optional; without it, the final checkpoint will be used.
from_hf_model:
type: string
description: The Hugging Face Hub repo to start training from. Should be as close as possible to the base model (specified by the `model` argument) in terms of architecture and size.
hf_model_revision:
type: string
description: The revision of the Hugging Face Hub model to continue training from. E.g., hf_model_revision=main (default, used if the argument is not provided) or hf_model_revision='607a30d783dfa663caf39e06633721c8d4cfcd7e' (specific commit).
hf_api_token:
type: string
description: The API token for the Hugging Face Hub.
hf_output_repo_name:
type: string
description: The name of the Hugging Face repository to upload the fine-tuned model to.
responses:
'200':
description: Fine-tuning job initiated successfully
content:
application/json:
schema:
$ref: '#/components/schemas/FinetuneResponseTruncated'
get:
tags:
- Fine-tuning
summary: List all jobs
description: List the metadata for all fine-tuning jobs. Returns a list of FinetuneResponseTruncated objects.
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: "# Docs for v1 can be found by changing the above selector ^\nfrom together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.list()\n\nfor fine_tune in response.data:\n print(f\"ID: {fine_tune.id}, Status: {fine_tune.status}\")\n"
- lang: Python
label: Together AI SDK (v1)
source: "from together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.list()\n\nfor fine_tune in response.data:\n print(f\"ID: {fine_tune.id}, Status: {fine_tune.status}\")\n"
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.list();\n\nfor (const fineTune of response.data) {\n console.log(fineTune.id, fineTune.status);\n}\n"
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.list();\n\nfor (const fineTune of response.data) {\n console.log(fineTune.id, fineTune.status);\n}\n"
- lang: Shell
label: cURL
source: "curl \"https://api.together.ai/v1/fine-tunes\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\"\n"
responses:
'200':
description: List of fine-tune jobs
content:
application/json:
schema:
$ref: '#/components/schemas/FinetuneTruncatedList'
/fine-tunes/estimate-price:
post:
tags:
- Fine-tuning
summary: Estimate price
description: Estimate the price of a fine-tuning job.
requestBody:
required: true
content:
application/json:
schema:
type: object
required:
- training_file
properties:
training_file:
type: string
description: File-ID of a training file uploaded to the Together API
validation_file:
type: string
description: File-ID of a validation file uploaded to the Together API
model:
type: string
description: Name of the base model to run fine-tune job on
n_epochs:
type: integer
default: 1
description: Number of complete passes through the training dataset (higher values may improve results but increase cost and risk of overfitting)
n_evals:
type: integer
default: 0
description: Number of evaluations to be run on a given validation set during training
training_method:
type: object
oneOf:
- $ref: '#/components/schemas/TrainingMethodSFT'
- $ref: '#/components/schemas/TrainingMethodDPO'
description: The training method to use. 'sft' for Supervised Fine-Tuning or 'dpo' for Direct Preference Optimization.
training_type:
type: object
default: null
nullable: true
oneOf:
- $ref: '#/components/schemas/FullTrainingType'
- $ref: '#/components/schemas/LoRATrainingType'
description: The training type to use. If not provided, the job will default to LoRA training type.
from_checkpoint:
type: string
description: The checkpoint identifier to continue training from a previous fine-tuning job. Format is `{$JOB_ID}` or `{$OUTPUT_MODEL_NAME}` or `{$JOB_ID}:{$STEP}` or `{$OUTPUT_MODEL_NAME}:{$STEP}`. The step value is optional; without it, the final checkpoint will be used.
responses:
'200':
description: Price estimated successfully
content:
application/json:
schema:
type: object
properties:
estimated_total_price:
type: number
description: The price of the fine-tuning job
allowed_to_proceed:
type: boolean
description: Whether the user is allowed to proceed with the fine-tuning job
example: true
user_limit:
type: number
description: The user's credit limit in dollars
estimated_train_token_count:
type: number
description: The estimated number of tokens to be trained
estimated_eval_token_count:
type: number
description: The estimated number of tokens for evaluation
'500':
description: Internal Server Error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
/fine-tunes/{id}:
get:
tags:
- Fine-tuning
summary: List job
description: List the metadata for a single fine-tuning job.
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: "# Docs for v1 can be found by changing the above selector ^\nfrom together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nfine_tune = client.fine_tuning.retrieve(id=\"ft-id\")\n\nprint(fine_tune)\n"
- lang: Python
label: Together AI SDK (v1)
source: "from together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nfine_tune = client.fine_tuning.retrieve(id=\"ft-id\")\n\nprint(fine_tune)\n"
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst fineTune = await client.fineTuning.retrieve(\"ft-id\");\n\nconsole.log(fineTune);\n"
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst fineTune = await client.fineTuning.retrieve(\"ft-id\");\n\nconsole.log(fineTune);\n"
- lang: Shell
label: cURL
source: "curl \"https://api.together.ai/v1/fine-tunes/ft-id\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\"\n"
parameters:
- name: id
in: path
required: true
schema:
description: The ID of the job to retrieve
type: string
responses:
'200':
description: Fine-tune job details retrieved successfully
content:
application/json:
schema:
$ref: '#/components/schemas/FinetuneResponse'
delete:
tags:
- Fine-tuning
summary: Delete a fine-tune job
description: Delete a fine-tuning job.
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: "# Docs for v1 can be found by changing the above selector ^\nfrom together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.delete(id=\"ft-id\")\n\nprint(response)\n"
- lang: Python
label: Together AI SDK (v1)
source: "from together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.delete(id=\"ft-id\")\n\nprint(response)\n"
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.delete(\"ft-id\");\n\nconsole.log(response);\n"
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.delete(\"ft-id\");\n\nconsole.log(response);\n"
- lang: Shell
label: cURL
source: "curl -X \"DELETE\" \"https://api.together.ai/v1/fine-tunes/ft-id?force=false\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\"\n"
parameters:
- name: id
in: path
required: true
schema:
description: The ID of the fine-tune job to delete
type: string
- name: force
deprecated: true
in: query
schema:
description: Deprecated and unused parameter.
type: boolean
default: false
responses:
'200':
description: Fine-tune job deleted successfully
content:
application/json:
schema:
$ref: '#/components/schemas/FinetuneDeleteResponse'
'404':
description: Fine-tune job not found
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
'500':
description: Internal server error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
/fine-tunes/{id}/events:
get:
tags:
- Fine-tuning
summary: List job events
description: List the events for a single fine-tuning job.
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: "# Docs for v1 can be found by changing the above selector ^\nfrom together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.list_events(id=\"ft-id\")\n\nfor event in response.data:\n print(event)\n"
- lang: Python
label: Together AI SDK (v1)
source: "from together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nevents = client.fine_tuning.list_events(id=\"ft-id\")\n\nprint(events)\n"
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst events = await client.fineTuning.listEvents(\"ft-id\");\n\nconsole.log(events);\n"
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst events = await client.fineTuning.listEvents(\"ft-id\");\n\nconsole.log(events);\n"
- lang: Shell
label: cURL
source: "curl \"https://api.together.ai/v1/fine-tunes/ft-id/events\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\"\n"
parameters:
- name: id
in: path
required: true
schema:
description: The ID of the fine-tune job to list events for
type: string
responses:
'200':
description: List of fine-tune events
content:
application/json:
schema:
$ref: '#/components/schemas/FinetuneListEvents'
/fine-tunes/{id}/checkpoints:
get:
tags:
- Fine-tuning
summary: List checkpoints
description: List the checkpoints for a single fine-tuning job.
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: "# Docs for v1 can be found by changing the above selector ^\nfrom together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\ncheckpoints = client.fine_tuning.list_checkpoints(id=\"ft-id\")\n\nprint(checkpoints)\n"
- lang: Python
label: Together AI SDK (v1)
source: "from together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\ncheckpoints = client.fine_tuning.list_checkpoints(id=\"ft-id\")\n\nprint(checkpoints)\n"
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst checkpoints = await client.fineTuning.listCheckpoints(\"ft-id\");\n\nconsole.log(checkpoints);\n"
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst checkpoints = await client.fineTuning.listCheckpoints(\"ft-id\");\n\nconsole.log(checkpoints);\n"
- lang: Shell
label: cURL
source: "curl \"https://api.together.ai/v1/fine-tunes/ft-id/checkpoints\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\"\n"
parameters:
- name: id
in: path
required: true
schema:
description: The ID of the fine-tune job to list checkpoints for
type: string
responses:
'200':
description: List of fine-tune checkpoints
content:
application/json:
schema:
$ref: '#/components/schemas/FinetuneListCheckpoints'
/finetune/download:
get:
tags:
- Fine-tuning
summary: Download model
description: Receive a compressed fine-tuned model or checkpoint.
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: "# Docs for v1 can be found by changing the above selector ^\nfrom together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\n# Using `with_streaming_response` gives you control to do what you want with the response.\nstream = client.fine_tuning.with_streaming_response.content(ft_id=\"ft-id\")\n\nwith stream as response:\n for line in response.iter_lines():\n print(line)\n"
- lang: Python
label: Together AI SDK (v1)
source: "from together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\n# This will download the content to a location on disk\nresponse = client.fine_tuning.download(id=\"ft-id\")\n\nprint(response)\n"
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.content({\n ft_id: \"ft-id\",\n});\n\nconsole.log(await response.blob());\n"
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.content({\n ft_id: \"ft-id\",\n});\n\nconsole.log(await response.blob());\n"
- lang: Shell
label: cURL
source: "curl \"https://api.together.ai/v1/finetune/download?ft_id=ft-id&checkpoint=merged\"\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\"\n"
parameters:
- in: query
name: ft_id
required: true
schema:
description: Fine-tune ID to download. A string that starts with `ft-`.
type: string
- in: query
name: checkpoint_step
required: false
schema:
description: Specifies step number for checkpoint to download. Ignores `checkpoint` value if set.
type: integer
- in: query
name: checkpoint
schema:
description: Specifies checkpoint type to download - `merged` vs `adapter`. This field is required if the checkpoint_step is not set.
type: string
enum:
- merged
- adapter
- model_output_path
responses:
'200':
description: Successfully downloaded the fine-tuned model or checkpoint.
content:
application/octet-stream:
schema:
type: string
format: binary
'400':
description: Invalid request parameters.
'404':
description: Fine-tune ID not found.
/fine-tunes/{id}/cancel:
post:
tags:
- Fine-tuning
summary: Cancel job
description: Cancel a currently running fine-tuning job. Returns a FinetuneResponseTruncated object.
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: "# Docs for v1 can be found by changing the above selector ^\nfrom together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.cancel(id=\"ft-id\")\n\nprint(response)\n"
- lang: Python
label: Together AI SDK (v1)
source: "from together import Together\nimport os\n\nclient = Together(\n api_key=os.environ.get(\"TOGETHER_API_KEY\"),\n)\n\nresponse = client.fine_tuning.cancel(id=\"ft-id\")\n\nprint(response)\n"
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.cancel(\"ft-id\");\n\nconsole.log(response);\n"
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: "import Together from \"together-ai\";\n\nconst client = new Together({\n apiKey: process.env.TOGETHER_API_KEY,\n});\n\nconst response = await client.fineTuning.cancel(\"ft-id\");\n\nconsole.log(response);\n"
- lang: Shell
label: cURL
source: "curl -X POST \"https://api.together.ai/v1/fine-tunes/ft-id/cancel\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\"\n"
parameters:
- name: id
in: path
required: true
schema:
description: Fine-tune ID to cancel. A string that starts with `ft-`.
type: string
responses:
'200':
description: Successfully cancelled the fine-tuning job.
content:
application/json:
schema:
$ref: '#/components/schemas/FinetuneResponseTruncated'
'400':
description: Invalid request parameters.
'404':
description: Fine-tune ID not found.
/fine-tunes/{id}/metrics:
get:
tags:
- Fine-tuning
summary: Get metrics
description: 'Retrieves recorded training metrics for a fine-tuning job in chronological order. All filter fields are optional — omit the body or send `{}` to retrieve all metrics.
'
x-codeSamples:
- lang: Shell
label: cURL
source: "curl -X GET \"https://api.together.ai/v1/fine-tunes/ft-id/metrics\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"global_step_from\": 0,\n \"global_step_to\": 500\n }'\n"
parameters:
- name: id
in: path
required: true
schema:
description: Fine-tune job ID. A string that starts with `ft-`.
type: string
requestBody:
required: false
content:
application/json:
schema:
type: object
properties:
global_step_from:
type: integer
format: int64
description: Return only metrics with global_step >= this value.
example: 0
global_step_to:
type: integer
format: int64
description: Return only metrics with global_step <= this value.
example: 500
logged_at_from:
type: string
format: date-time
description: Return only metrics logged at or after this ISO-8601 timestamp.
example: '2024-01-01T00:00:00Z'
logged_at_to:
type: string
format: date-time
description: Return only metrics logged at or before this ISO-8601 timestamp.
example: '2024-01-01T12:00:00Z'
resolution:
type: integer
format: int64
description: Number of (uniformly sampled) train metrics to return.
example: 100
responses:
'200':
description: List of metrics snapshots in chronological order.
content:
application/json:
schema:
type: object
properties:
metrics:
type: array
items:
type: object
additionalProperties:
type: number
description: A flat dictionary of scalar metric values.
example:
metrics:
- train/loss: 0.5
train/learning_rate: 0.0001
train/global_step: 7
- train/loss: 0.45
train/learning_rate: 9.0e-05
train/global_step: 14
'400':
description: Invalid request — bad JSON body or missing job ID.
'404':
description: Fine-tune job not found.
'500':
description: Internal server error — failed to retrieve metrics.
/fine-tunes/models/supported:
get:
tags:
- Fine-tuning
summary: List supported models
description: List models supported for fine-tuning.
x-codeSamples:
- lang: Shell
label: cURL (list all)
source: "curl \"https://api.together.ai/v1/fine-tunes/models/supported\" \\\n -H \"Authorization: Bearer $TOGETHER_API_KEY\"\n"
responses:
'200':
description: List of supported models.
content:
application/json:
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# Full source: https://raw.githubusercontent.com/api-evangelist/together-ai/refs/heads/main/openapi/together-ai-fine-tuning-api-openapi.yml